W4 - Clustering and Similarity - Retrieving Documents - Trainee.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 위키피디아 데이터에서 문서 찾기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Graphlab\n",
    "\n",
    "graphlab을 import합니다. 에러가 나는 경우 'install graphlab' 노트북을 열어서 설치해야 합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "import graphlab"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 데이터 화일 업로드하기\n",
    "\n",
    "먼저 people_wiki.gl.zip 화일을 업로드합니다. Destination Folder에 /library/data 폴더를 지정합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ls 명령을 이용해서 data 폴더 안에 people_wiki.gl.zip 화일이 제대로 업로드되었는지 확인합시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0m\u001b[01;34mamazon_baby.gl\u001b[0m/     \u001b[01;34mhome_data.gl\u001b[0m/     kaggle_titanic.zip\r\n",
      "amazon_baby.gl.zip  home_data.gl.zip  \u001b[01;34mpeople_wiki.gl\u001b[0m/\r\n",
      "data.ipynb          \u001b[01;34mkaggle_titanic\u001b[0m/   people_wiki.gl.zip\r\n"
     ]
    }
   ],
   "source": [
    "ls ../data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "이제 unzip 명령을 이용해서 압축화일을 해제합시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Archive:  ../data/song_data.gl.zip\n",
      "  End-of-central-directory signature not found.  Either this file is not\n",
      "  a zipfile, or it constitutes one disk of a multi-part archive.  In the\n",
      "  latter case the central directory and zipfile comment will be found on\n",
      "  the last disk(s) of this archive.\n",
      "unzip:  cannot find zipfile directory in one of ../data/song_data.gl.zip or\n",
      "        ../data/song_data.gl.zip.zip, and cannot find ../data/song_data.gl.zip.ZIP, period.\n"
     ]
    }
   ],
   "source": [
    "!unzip -o ../data/song_data.gl.zip -d ../data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 위키피디아에서 인물에 대한 텍스트 데이터를 로드합니다.\n",
    "\n",
    "위키피디아의 인물에 대한 텍스트 데이터를 읽어 들입니다.\n",
    "\n",
    "SFrame 데이터를 읽어 와서 **people**이라는 변수에 저장합니다.\n",
    "**'../data/people_wiki.gl/'**이라는 폴더를 지정해야 합니다.\n",
    "\n",
    "    graphlab.SFrame(폴더위치)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "people = graphlab.SFrame('../data/people_wiki.gl/')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "head 메소드로 people에 어떤 데이터가 들어 있는지 확인해 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method SFrame.head of Columns:\n",
       "\tURI\tstr\n",
       "\tname\tstr\n",
       "\ttext\tstr\n",
       "\n",
       "Rows: 59071\n",
       "\n",
       "Data:\n",
       "+-------------------------------+---------------------+\n",
       "|              URI              |         name        |\n",
       "+-------------------------------+---------------------+\n",
       "| <http://dbpedia.org/resour... |    Digby Morrell    |\n",
       "| <http://dbpedia.org/resour... |    Alfred J. Lewy   |\n",
       "| <http://dbpedia.org/resour... |    Harpdog Brown    |\n",
       "| <http://dbpedia.org/resour... | Franz Rottensteiner |\n",
       "| <http://dbpedia.org/resour... |        G-Enka       |\n",
       "| <http://dbpedia.org/resour... |    Sam Henderson    |\n",
       "| <http://dbpedia.org/resour... |    Aaron LaCrate    |\n",
       "| <http://dbpedia.org/resour... |   Trevor Ferguson   |\n",
       "| <http://dbpedia.org/resour... |     Grant Nelson    |\n",
       "| <http://dbpedia.org/resour... |     Cathy Caruth    |\n",
       "+-------------------------------+---------------------+\n",
       "+-------------------------------+\n",
       "|              text             |\n",
       "+-------------------------------+\n",
       "| digby morrell born 10 octo... |\n",
       "| alfred j lewy aka sandy le... |\n",
       "| harpdog brown is a singer ... |\n",
       "| franz rottensteiner born i... |\n",
       "| henry krvits born 30 decem... |\n",
       "| sam henderson born october... |\n",
       "| aaron lacrate is an americ... |\n",
       "| trevor ferguson aka john f... |\n",
       "| grant nelson born 27 april... |\n",
       "| cathy caruth born 1955 is ... |\n",
       "+-------------------------------+\n",
       "[59071 rows x 3 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.>"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "people.head"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "위키피디아 문서로 가는 링크, 인물의 이름, 문서의 텍스트 등이 들어 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "총 몇명의 데이터인지 확인해 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "59071"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(people)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "59,701명이 맞나요?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 데이터셋을 살펴보고 어떤 텍스트가 있는지 확인해 봅시다.\n",
    "\n",
    "## Obama 대통령의 데이터를 확인해 봅시다.\n",
    "\n",
    "전체 인물 데이터에서 Obama 대통령에 해당하는 데이터를 찾아서 **obama**에 저장합시다. 이름에서 'Barack Obama'를 찾으면 됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "obama = people[people['name']=='Barack Obama']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "obama의 데이터를 확인해 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">URI</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">name</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">text</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">&lt;http://dbpedia.org/resou<br>rce/Barack_Obama&gt; ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Barack Obama</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">barack hussein obama ii<br>brk husen bm born august ...</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[? rows x 3 columns]<br/>Note: Only the head of the SFrame is printed. This SFrame is lazily evaluated.<br/>You can use sf.materialize() to force materialization.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tURI\tstr\n",
       "\tname\tstr\n",
       "\ttext\tstr\n",
       "\n",
       "Rows: Unknown\n",
       "\n",
       "Data:\n",
       "+-------------------------------+--------------+-------------------------------+\n",
       "|              URI              |     name     |              text             |\n",
       "+-------------------------------+--------------+-------------------------------+\n",
       "| <http://dbpedia.org/resour... | Barack Obama | barack hussein obama ii br... |\n",
       "+-------------------------------+--------------+-------------------------------+\n",
       "[? rows x 3 columns]\n",
       "Note: Only the head of the SFrame is printed. This SFrame is lazily evaluated.\n",
       "You can use sf.materialize() to force materialization."
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obama"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "obama의 **'text'** 컬럼의 데이터를 확인해 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype: str\n",
       "Rows: ?\n",
       "['barack hussein obama ii brk husen bm born august 4 1961 is the 44th and current president of the united states and the first african american to hold the office born in honolulu hawaii obama is a graduate of columbia university and harvard law school where he served as president of the harvard law review he was a community organizer in chicago before earning his law degree he worked as a civil rights attorney and taught constitutional law at the university of chicago law school from 1992 to 2004 he served three terms representing the 13th district in the illinois senate from 1997 to 2004 running unsuccessfully for the united states house of representatives in 2000in 2004 obama received national attention during his campaign to represent illinois in the united states senate with his victory in the march democratic party primary his keynote address at the democratic national convention in july and his election to the senate in november he began his presidential campaign in 2007 and after a close primary campaign against hillary rodham clinton in 2008 he won sufficient delegates in the democratic party primaries to receive the presidential nomination he then defeated republican nominee john mccain in the general election and was inaugurated as president on january 20 2009 nine months after his election obama was named the 2009 nobel peace prize laureateduring his first two years in office obama signed into law economic stimulus legislation in response to the great recession in the form of the american recovery and reinvestment act of 2009 and the tax relief unemployment insurance reauthorization and job creation act of 2010 other major domestic initiatives in his first term included the patient protection and affordable care act often referred to as obamacare the doddfrank wall street reform and consumer protection act and the dont ask dont tell repeal act of 2010 in foreign policy obama ended us military involvement in the iraq war increased us troop levels in afghanistan signed the new start arms control treaty with russia ordered us military involvement in libya and ordered the military operation that resulted in the death of osama bin laden in january 2011 the republicans regained control of the house of representatives as the democratic party lost a total of 63 seats and after a lengthy debate over federal spending and whether or not to raise the nations debt limit obama signed the budget control act of 2011 and the american taxpayer relief act of 2012obama was reelected president in november 2012 defeating republican nominee mitt romney and was sworn in for a second term on january 20 2013 during his second term obama has promoted domestic policies related to gun control in response to the sandy hook elementary school shooting and has called for full equality for lgbt americans while his administration has filed briefs which urged the supreme court to strike down the defense of marriage act of 1996 and californias proposition 8 as unconstitutional in foreign policy obama ordered us military involvement in iraq in response to gains made by the islamic state in iraq after the 2011 withdrawal from iraq continued the process of ending us combat operations in afghanistan and has sought to normalize us relations with cuba', ... ]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obama['text']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **대배우님**, George Clooney의 데이터를 살펴 봅시다.\n",
    "\n",
    "'George Clooney'의 데이터를 찾아서 **clooney**에 저장합시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "clooney = people[people['name'] == 'George Clooney']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "text 컬럼의 데이터를 확인해 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype: str\n",
       "Rows: ?\n",
       "['george timothy clooney born may 6 1961 is an american actor writer producer director and activist he has received three golden globe awards for his work as an actor and two academy awards one for acting and the other for producingclooney made his acting debut on television in 1978 and later gained wide recognition in his role as dr doug ross on the longrunning medical drama er from 1994 to 1999 for which he received two emmy award nominations while working on er he began attracting a variety of leading roles in films including the superhero film batman robin 1997 and the crime comedy out of sight 1998 in which he first worked with a director who would become a longtime collaborator steven soderbergh in 1999 clooney took the lead role in three kings a wellreceived war satire set during the gulf warin 2001 clooneys fame widened with the release of his biggest commercial success the heist comedy oceans eleven the first of the film trilogy a remake of the 1960 film with frank sinatra as danny ocean he made his directorial debut a year later with the biographical thriller confessions of a dangerous mind and has since directed the drama good night and good luck 2005 the sports comedy leatherheads 2008 the political drama the ides of march 2011 and the comedydrama war film the monuments men 2014he won an academy award for best supporting actor for the middle east thriller syriana 2005 and subsequently earned best actor nominations for the legal thriller michael clayton 2007 the comedydrama up in the air 2009 and the drama the descendants 2011 in 2013 he received the academy award for best picture for producing the political thriller argo alongside ben affleck and grant heslov he is the only person ever to be nominated for academy awards in six categoriesclooney is sometimes described as one of the most handsome men in the world in 2005 tv guide ranked clooney no 1 on its 50 sexiest stars of all time list in 2009 he was included in times annual time 100 as one of the most influential people in the world clooney is also noted for his political activism and has served as one of the united nations messengers of peace since january 31 2008 his humanitarian work includes his advocacy of finding a resolution for the darfur conflict raising funds for the 2010 haiti earthquake 2004 tsunami and 911 victims and creating documentaries such as sand and sorrow to raise awareness about international crises he is also a member of the council on foreign relations', ... ]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clooney['text']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Obama 문서의 단어 카운트를 만들어 봅시다.\n",
    "\n",
    "\n",
    "이제 아래 메소드를 사용해서 Obama 문서의 단어 개수 벡터를 만든 다음, **word_count**라는 컬럼으로 obama에 저장해 봅시다.\n",
    "\n",
    "    graphlab.text_analytics.count_words(SArray)\n",
    "\n",
    "주의: 이 메소드는 SFrame이 아니라 SArray를 입력으로 받습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "type(obama['text'])\n",
    "obama['word_count'] = graphlab.text_analytics.count_words(obama['text'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**'word_count'** 컬럼을 출력해서 내용을 살펴 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype: dict\n",
       "Rows: 1\n",
       "[{'operations': 1, 'represent': 1, 'office': 2, 'unemployment': 1, 'is': 2, 'doddfrank': 1, 'over': 1, 'unconstitutional': 1, 'domestic': 2, 'named': 1, 'ending': 1, 'ended': 1, 'proposition': 1, 'seats': 1, 'graduate': 1, 'worked': 1, 'before': 1, 'death': 1, '20': 2, 'taxpayer': 1, 'inaugurated': 1, 'obamacare': 1, 'civil': 1, 'mccain': 1, 'to': 14, '4': 1, 'policy': 2, '8': 1, 'has': 4, '2011': 3, '2010': 2, '2013': 1, '2012': 1, 'bin': 1, 'then': 1, 'his': 11, 'march': 1, 'gains': 1, 'cuba': 1, 'californias': 1, '1992': 1, 'new': 1, 'not': 1, 'during': 2, 'years': 1, 'continued': 1, 'presidential': 2, 'husen': 1, 'osama': 1, 'term': 3, 'equality': 1, 'prize': 1, 'lost': 1, 'stimulus': 1, 'january': 3, 'university': 2, 'rights': 1, 'gun': 1, 'republican': 2, 'rodham': 1, 'troop': 1, 'withdrawal': 1, 'involvement': 3, 'response': 3, 'where': 1, 'referred': 1, 'affordable': 1, 'attorney': 1, 'school': 3, 'senate': 3, 'house': 2, 'national': 2, 'creation': 1, 'related': 1, 'hawaii': 1, 'born': 2, 'second': 2, 'street': 1, 'election': 3, 'close': 1, 'operation': 1, 'insurance': 1, 'sandy': 1, 'afghanistan': 2, 'initiatives': 1, 'for': 4, 'reform': 1, 'federal': 1, 'review': 1, 'representatives': 2, 'debate': 1, 'current': 1, 'state': 1, 'won': 1, 'marriage': 1, 'victory': 1, 'unsuccessfully': 1, 'reauthorization': 1, 'keynote': 1, 'full': 1, 'patient': 1, 'august': 1, 'degree': 1, '44th': 1, 'bm': 1, 'mitt': 1, 'attention': 1, 'delegates': 1, 'lgbt': 1, 'job': 1, 'protection': 2, 'address': 1, 'ask': 1, 'november': 2, 'debt': 1, 'by': 1, 'care': 1, 'on': 2, 'great': 1, 'defense': 1, 'signed': 3, 'libya': 1, 'receive': 1, 'of': 18, 'months': 1, 'against': 1, 'foreign': 2, 'spending': 1, 'american': 3, 'harvard': 2, 'act': 8, 'military': 4, 'hussein': 1, 'or': 1, 'first': 3, 'and': 21, 'major': 1, 'clinton': 1, '1997': 1, 'campaign': 3, 'russia': 1, 'wall': 1, 'legislation': 1, 'into': 1, 'primary': 2, 'community': 1, 'three': 1, 'down': 1, 'hook': 1, 'ii': 1, '63': 1, 'americans': 1, 'elementary': 1, 'total': 1, 'earning': 1, 'often': 1, 'barack': 1, 'law': 6, 'from': 3, 'raise': 1, 'district': 1, 'representing': 1, 'nine': 1, 'reinvestment': 1, 'arms': 1, 'relations': 1, 'nobel': 1, 'start': 1, 'dont': 2, 'tell': 1, 'iraq': 4, 'convention': 1, 'strike': 1, 'served': 2, 'john': 1, 'was': 5, 'war': 1, 'form': 1, 'that': 1, 'tax': 1, 'sufficient': 1, 'republicans': 1, 'resulted': 1, 'hillary': 1, 'taught': 1, 'honolulu': 1, 'filed': 1, 'regained': 1, 'july': 1, 'hold': 1, 'with': 3, 'he': 7, '13th': 1, 'made': 1, 'brk': 1, '1996': 1, 'whether': 1, 'reelected': 1, 'budget': 1, 'us': 6, 'nations': 1, 'recession': 1, 'while': 1, 'economic': 1, 'limit': 1, 'policies': 1, 'promoted': 1, 'called': 1, 'at': 2, 'control': 4, 'supreme': 1, 'ordered': 3, 'nominee': 2, 'process': 1, '2000in': 1, '2012obama': 1, 'received': 1, 'romney': 1, 'briefs': 1, 'defeated': 1, 'general': 1, 'states': 3, 'as': 6, 'urged': 1, 'in': 30, 'sought': 1, 'organizer': 1, 'shooting': 1, 'increased': 1, 'normalize': 1, 'lengthy': 1, 'united': 3, 'court': 1, 'recovery': 1, 'laden': 1, 'laureateduring': 1, 'peace': 1, 'administration': 1, '1961': 1, 'illinois': 2, 'other': 1, 'which': 1, 'party': 3, 'primaries': 1, 'sworn': 1, '2007': 1, 'obama': 9, 'columbia': 1, 'combat': 1, 'after': 4, 'islamic': 1, 'running': 1, 'levels': 1, 'two': 1, 'included': 1, 'president': 4, 'repeal': 1, 'nomination': 1, 'the': 40, 'a': 7, '2009': 3, 'chicago': 2, 'constitutional': 1, 'defeating': 1, 'treaty': 1, 'relief': 2, '2004': 3, 'african': 1, '2008': 1, 'democratic': 4, 'consumer': 1, 'began': 1, 'terms': 1}]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obama['word_count']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "관련 문서의 텍스트를 분석하여 등장한 단어를 키(key)로, 단어가 나타난 개수를 값(value)으로 하는 dictionary 형태임을 알 수 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obama 문서의 단어 카운트를 소팅하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 단어 카운트 dictionary를 테이블로 변환하기\n",
    "word_count 컬럼에 저장되어 있는 dictionary를 stack 메소드를 이용해서 단어를 'word' 컬럼에, 횟수를 'count' 컬럼에 넣습니다. stack 메소드는 주어진 SFrame에 새로운 컬럼들을 추가해서 **각 단어별로** 반환합니다.\n",
    "\n",
    "    SFrame.stack(컬럼이름, new_column_name=새로운컬럼이름리스트)\n",
    "\n",
    "주의: **obama 문서의 'word_count' 컬럼만으로 만들어진 SFrame**을 이용하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">word</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">cuba</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">relations</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">sought</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">combat</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">ending</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">withdrawal</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">state</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">islamic</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">by</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">gains</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[273 rows x 2 columns]<br/>Note: Only the head of the SFrame is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tword\tstr\n",
       "\tcount\tint\n",
       "\n",
       "Rows: 273\n",
       "\n",
       "Data:\n",
       "+------------+-------+\n",
       "|    word    | count |\n",
       "+------------+-------+\n",
       "|    cuba    |   1   |\n",
       "| relations  |   1   |\n",
       "|   sought   |   1   |\n",
       "|   combat   |   1   |\n",
       "|   ending   |   1   |\n",
       "| withdrawal |   1   |\n",
       "|   state    |   1   |\n",
       "|  islamic   |   1   |\n",
       "|     by     |   1   |\n",
       "|   gains    |   1   |\n",
       "+------------+-------+\n",
       "[273 rows x 2 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(obama['word_count'])\n",
    "obama[['word_count']].stack('word_count', new_column_name=['word', 'count'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "이 결과를 **obama_word_count_table**에 저장하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "obama_word_count_table = obama[['word_count']].stack('word_count', new_column_name=['word', 'count'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 맨위에 가장 많이 나오는 단어가 나오도록 단어 카운트 소팅하기\n",
    "\n",
    "먼저 head 메소드를 이용해서 obama_word_count_table의 내용을 확인합시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method SFrame.head of Columns:\n",
       "\tword\tstr\n",
       "\tcount\tint\n",
       "\n",
       "Rows: 273\n",
       "\n",
       "Data:\n",
       "+------------+-------+\n",
       "|    word    | count |\n",
       "+------------+-------+\n",
       "|    cuba    |   1   |\n",
       "| relations  |   1   |\n",
       "|   sought   |   1   |\n",
       "|   combat   |   1   |\n",
       "|   ending   |   1   |\n",
       "| withdrawal |   1   |\n",
       "|   state    |   1   |\n",
       "|  islamic   |   1   |\n",
       "|     by     |   1   |\n",
       "|   gains    |   1   |\n",
       "+------------+-------+\n",
       "[273 rows x 2 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obama_word_count_table.head"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "이제 'count' 컬럼의 값에 따라 내림차순으로 소팅해 주세요.\n",
    "\n",
    "    SFrame.sort(컬럼이름, ascending=True또는False)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">word</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">the</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">in</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">and</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">of</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">to</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">his</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">obama</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">act</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">he</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">a</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">7</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[273 rows x 2 columns]<br/>Note: Only the head of the SFrame is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tword\tstr\n",
       "\tcount\tint\n",
       "\n",
       "Rows: 273\n",
       "\n",
       "Data:\n",
       "+-------+-------+\n",
       "|  word | count |\n",
       "+-------+-------+\n",
       "|  the  |   40  |\n",
       "|   in  |   30  |\n",
       "|  and  |   21  |\n",
       "|   of  |   18  |\n",
       "|   to  |   14  |\n",
       "|  his  |   11  |\n",
       "| obama |   9   |\n",
       "|  act  |   8   |\n",
       "|   he  |   7   |\n",
       "|   a   |   7   |\n",
       "+-------+-------+\n",
       "[273 rows x 2 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obama_word_count_table.sort('count', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "많이 등장하는 단어들에는 정보로서의 가치가 없는 단어들 - \"the\", \"in\", \"and\" 등 - 이 다수 포함되어 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Corpus의 TF-IDF 계산하기 \n",
    "\n",
    "정보로서 가치가 있는 단어들에 더 많은 weight를 주기 위해 TF-IDF 점수를 이용하고자 합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "개별 인물이 아닌, 전체 corpus에 대해서 적용해 봅시다.\n",
    "\n",
    "아래 메소드를 이용해서 people 문서의 텍스트에 대한 단어 개수 벡터를 만든 다음, **word_count**라는 컬럼으로 people에 저장해 봅시다.\n",
    "\n",
    "    graphlab.text_analytics.count_words(SArray)\n",
    "\n",
    "주의: 이 메소드는 SFrame이 아니라 SArray를 입력으로 받습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "people['word_count'] = graphlab.text_analytics.count_words(people['text'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "head 메소드를 이용해서 내용을 확인합시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "print people['word_count']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "아래 메소드에 **word_count**를 인자로 넣어서 TF_IDF를 구한 다음, **tdidf**라는 컬럼으로 people에 저장합시다.\n",
    "    \n",
    "    graphlab.text_analytics.tf_idf(SArray)\n",
    "    \n",
    "주의: 이 메소드는 SFrame이 아니라 SArray를 입력으로 받습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "people['tfidf'] = graphlab.text_analytics.tf_idf(people['word_count'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "마찬가지로 head로 내용을 확인합시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method SArray.head of dtype: dict\n",
       "Rows: 59071\n",
       "[{'selection': 3.836578553093086, 'carltons': 7.0744723837970485, 'being': 1.7938099524877322, '2005': 1.6425861253275964, 'coach': 5.444264118987054, 'its': 1.6875948402695313, 'before': 2.9935647453367427, '21': 2.797250863489293, 'northern': 3.310021742836038, 'bullants': 7.489987827758714, 'to': 0.23472468840899613, 'perth': 5.051601193605607, 'sydney': 3.5981675296480873, '2014': 2.2073995783446634, 'has': 0.428497539744039, '2011': 1.7023470901042919, '2013': 1.9545642372230505, 'division': 2.7906099979103978, 'his': 0.7878343656409719, 'rules': 3.8272034844276295, 'assistant': 2.5220702633476124, 'spanned': 5.531174273867493, 'early': 1.929422753652229, 'game': 2.4168995190159084, 'five': 2.2137301792754096, 'during': 1.3174651479035495, 'continued': 2.720588055069447, '44game': 9.887883100557085, 'kangaroos': 20.726873835958425, 'twice': 3.3301582227950113, 'round': 2.897933583948961, 'the': 0.0027426017494956603, 'parade': 5.510031837293684, 'born': 0.268196273764765, 'clubs': 3.4464050690798693, 'college': 1.5613662703175555, 'blues': 4.064837205074066, 'for': 0.29145011737314763, 'falcons': 5.868501576808439, 'currently': 1.637088969126014, 'hill': 3.794313330511949, 'drawn': 4.96062941539988, 'cause': 4.8023464982877115, 'kicked': 5.142950972193835, 'exchange': 4.113331555012676, 'mckernan': 9.600201028105303, '19982000': 6.509158574746988, 'brisbaneafter': 10.986495389225194, 'losing': 3.773463729390325, 'essendon': 6.016682089649193, 'along': 2.5088749729287803, 'teaches': 3.7712554104950966, 'by': 0.37455341206197373, 'box': 4.576320507259028, 'league': 8.342695137239867, 'career': 1.3050270203415668, 'of': 0.016624704796446097, 'against': 4.015921958283749, 'david': 2.4512658353228582, 'melbourne': 3.8914310119380633, 'digby': 8.347438059609935, 'games': 2.2331239682242914, 'leading': 5.061504320250359, 'traded': 3.952107459309691, 'first': 0.6956048713993103, 'goalkicker': 6.859361004180102, 'morrell': 46.88528738395547, 'corey': 6.486685718894929, 'acted': 4.137429106591736, 'football': 25.58570665567139, 'carlton': 10.682096983163913, 'from': 0.5875106759712689, 'district': 2.774469584601757, 'west': 5.205210090246754, 'hawks': 5.531174273867493, 'draft': 3.240194726993755, 'coburg': 7.851001173296044, 'forward': 3.8848194176057507, 'australian': 8.630007339620153, 'was': 0.3968289280609173, 'until': 1.7591012626831841, 'shifted': 5.634637255749128, 'club': 11.043158373020127, 'season': 5.6626008156972025, 'vflaffiliate': 7.431147327735781, 'western': 3.0880842964135953, 'with': 1.0123432126103034, 'former': 1.3573131120992086, 'he': 1.280211345952344, '10': 2.3157231098806563, 'october': 1.9182947844101343, '1979': 2.6032908378122737, 'recruited': 4.4897203990393315, 'victorian': 4.564873121418676, 'played': 4.636320601315451, '32': 4.3717697890214335, 'following': 1.9609195556941061, 'teague': 9.04058524016988, 'and': 0.002980575592194913, 'footballer': 3.2388985505323085, 'strathmore': 8.588600116426823, 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5.522422295712894, 'switch': 5.658619220435613, 'member': 1.2204325126007385, 'also': 0.4627270916162349, 'vancouver': 8.438304527919604, 'policiesbeginning': 10.986495389225194, 'instead': 3.8056641901806385, 'clarks': 6.843360662833661, 'columbia': 12.929771000757748, 'minority': 4.6496696580787535, 'provincial': 8.42454300573516, 'who': 1.8197904379608427, 'leftleaning': 7.895452935866879, 'coming': 3.7624705809393637, 'strahl': 10.293348208665249, 'a': 0.0730493981435809, 'emersons': 9.377057476791094, '1977': 2.6962027980008787, '1974': 2.77067759739274, 'revolt': 7.054669756500869, '1972': 2.8070152038663028, 'disagreeing': 8.501588739437194, 'chief': 2.552031845407953, '2001': 1.9280249665871378, '2006': 3.041475810769012, 'firestorm': 8.683910296231149, '2005': 1.6425861253275964, 'the': 0.0025394460643478334, 'having': 2.448323791423765, 'vancouversunshine': 9.600201028105303}, {'coach': 2.722132059493527, 'managed': 3.5225587847562694, 'vfagrieg': 10.986495389225194, 'is': 0.02761625047551999, 'polled': 6.199003646443148, 'years': 1.0752380994247055, 'whilst': 4.442583543660402, 'carltona': 10.986495389225194, 'fine': 3.577964822330568, 'its': 5.062784520808594, 'onset': 6.926052378678775, 'votes': 3.7875641485370206, '21': 2.797250863489293, '23': 5.938375763073227, 'had': 2.354856824617116, 'winning': 2.416330313042851, 'to': 0.2816696260907954, 'only': 1.819375719703575, 'award': 1.6322278484423687, 'under': 1.8347379746813095, 'suffered': 4.044338683525725, 'team': 1.7320424426306904, 'footballer': 3.2388985505323085, 'suburban': 5.7290000171974125, 'his': 0.7878343656409719, 'preseason': 5.233922750399561, 'rules': 3.8272034844276295, 'compiled': 4.870603263742161, 'handballs': 8.421546031763658, 'nearly': 3.8452502668747033, 'despite': 3.327324021559136, 'not': 3.1760341502672342, 'during': 1.3174651479035495, 'listin': 7.552508184740048, 'him': 3.1511686535743872, 'association': 2.1546374540272892, 'name': 2.433549028103139, 'captaining': 6.411784410721811, 'did': 2.318987437150089, 'debut': 2.1723135660368764, 'wish': 5.489327163931993, 'noted': 3.443222042519748, 'the': 0.0015236676386087002, 'dean': 3.7016744766565908, 'ten': 2.9294347072594293, 'griegs': 8.789270811888976, 'some': 2.1974446757041473, 'mishap': 8.683910296231149, 'born': 0.268196273764765, 'clubs': 3.4464050690798693, 'best': 1.5336010724149785, 'out': 1.8484031814566355, 'for': 0.29145011737314763, 'creative': 3.464636137023565, 'progress': 4.767895269533465, 'be': 1.4062480045415613, 'after': 0.9443334420013064, 'leg': 9.728005159421617, 'greig': 7.895452935866879, 'sole': 5.030658019760364, '19s': 8.042056410058754, 'broken': 4.4212304191898335, 'disposals': 6.2679965179301, 'by': 0.37455341206197373, 'trophy': 4.378494763929107, 'on': 0.18441275335060037, '39': 5.020348650101503, 'last': 2.407078854628825, 'of': 0.012468528597334574, '31': 3.294838566414648, 'changed': 3.9725799144146667, 'against': 2.0079609791418744, 'round': 2.897933583948961, 'games': 4.466247936448583, 'collingwood': 5.982549083279735, 'retain': 5.653776595959825, 'and': 0.004470863388292369, 'kilda': 11.96509816655947, 'gary': 4.004560712068805, 'ailing': 7.225295273531632, 'midfielder': 4.804410482508563, '1985': 5.064910025628451, 'described': 3.1584573570993646, 'due': 2.7324867986603505, 'handballin': 10.293348208665249, 'brice': 8.153282045168979, 'expected': 4.866197970274244, 'australian': 8.630007339620153, 'recruited': 8.979440798078663, 'fairest': 5.653776595959825, 'league': 6.2570213529299, 'club': 6.625895023812077, 'season': 1.8875336052324008, 'but': 1.313994565464302, 'released': 2.0078348995855078, 'kicks': 6.224321454427438, 'with': 0.20246864252206068, 'former': 1.3573131120992086, 'he': 1.06684278829362, '1991': 4.750167045139951, '1990': 4.736742958461033, 'october': 1.9182947844101343, '16': 2.680270173193033, 'this': 1.2818856957987381, 'was': 0.2380973568365504, 'j': 6.511762646322909, 'record': 2.1528869065343033, 'victorian': 9.129746242837353, 'nine': 3.2624907325491286, 'performances': 3.352641829543426, 'following': 1.9609195556941061, 'didnt': 4.383907497035858, 'strongly': 4.925038470297177, 'played': 3.0908804008769675, 'winless': 7.585298007563039, 'turned': 3.394129260705398, 'it': 1.3165805834938153, 'an': 0.2982390890818971, '1980s': 2.9688582293167167, 'as': 0.2543390440248236, 'hawthorn': 12.253365969727044, 'at': 0.645957859962386, 'in': 0.009654063501214493, 'leaguegreig': 10.293348208665249, 'end': 2.419560105914143, 'built': 4.061882993176634, 'liston': 7.654290879049991, 'amputated': 7.895452935866879, 'also': 0.4627270916162349, '2001': 1.9280249665871378, 'which': 1.5348619340875385, 'gangrene': 9.600201028105303, 'shining': 6.696035948076803, 'scoresby': 9.377057476791094, 'football': 17.909994658969975, 'infection': 6.766987684049088, 'camberwell': 14.979975655517428, '1968': 2.8997774689212887, 'subsequently': 2.8793779184748045, 'a': 0.02809592236291573, 'lower': 4.515695885442592, 'vfl': 10.506308224654898, 'onfield': 7.690658523220865, 'grieg': 7.585298007563039, 'nevertheless': 5.505856465883203, 'light': 3.740840321630659, 'age': 2.138848033513307, 'st': 5.02274994846173, 'trialled': 8.907053847545358, 'senior': 2.2990532222492712, 'playing': 2.0910027577735617}, ... ]>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "people['tfidf'].head"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obama 문서의 TF-IDF 살펴보기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "people에서 Obama 문서를 골라내서 **obama**라는 변수에 저장합시다. 'Barack Obama'를 사용하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "obama = people[people['name']=='Barack Obama']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "obama를 출력해 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">URI</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">name</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">text</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">word_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">&lt;http://dbpedia.org/resou<br>rce/Barack_Obama&gt; ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Barack Obama</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">barack hussein obama ii<br>brk husen bm born august ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">{'operations': 1,<br>'represent': 1, 'offi ...</td>\n",
       "    </tr>\n",
       "</table>\n",
       "<table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">tfidf</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">{'operations':<br>3.811771079388818, ...</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[? rows x 5 columns]<br/>Note: Only the head of the SFrame is printed. This SFrame is lazily evaluated.<br/>You can use sf.materialize() to force materialization.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tURI\tstr\n",
       "\tname\tstr\n",
       "\ttext\tstr\n",
       "\tword_count\tdict\n",
       "\ttfidf\tdict\n",
       "\n",
       "Rows: Unknown\n",
       "\n",
       "Data:\n",
       "+-------------------------------+--------------+-------------------------------+\n",
       "|              URI              |     name     |              text             |\n",
       "+-------------------------------+--------------+-------------------------------+\n",
       "| <http://dbpedia.org/resour... | Barack Obama | barack hussein obama ii br... |\n",
       "+-------------------------------+--------------+-------------------------------+\n",
       "+-------------------------------+-------------------------------+\n",
       "|           word_count          |             tfidf             |\n",
       "+-------------------------------+-------------------------------+\n",
       "| {'operations': 1, 'represe... | {'operations': 3.811771079... |\n",
       "+-------------------------------+-------------------------------+\n",
       "[? rows x 5 columns]\n",
       "Note: Only the head of the SFrame is printed. This SFrame is lazily evaluated.\n",
       "You can use sf.materialize() to force materialization."
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obama"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TF-IDF dictionary를 테이블로 변환하기\n",
    "'tfidf'컬럼에 저장되어 있는 dictionary를 stack 메소드를 이용해서 단어를 'word' 컬럼에, tf-idf점수를 'tfidf' 컬럼에 넣어 봅시다. stack 메소드는 주어진 SFrame에 새로운 컬럼들을 추가해서 **각 단어별로** 반환합니다.\n",
    "\n",
    "    SFrame.stack(컬럼이름, new_column_name=새로운컬럼이름리스트)\n",
    "\n",
    "주의: **obama 문서의 'tfidf' 컬럼만으로 만들어진 SFrame**을 이용하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">word</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">tfidf</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">melbourne</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3.89143101194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">college</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1.56136627032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">parade</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5.51003183729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">education</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2.4487155642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">teaches</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3.7712554105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">currently</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1.63708896913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">edflhe</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10.9864953892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">also</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.462727091616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">coburg</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">7.8510011733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">coached</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3.992562414</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[10379283 rows x 2 columns]<br/>Note: Only the head of the SFrame is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tword\tstr\n",
       "\ttfidf\tfloat\n",
       "\n",
       "Rows: 10379283\n",
       "\n",
       "Data:\n",
       "+-----------+----------------+\n",
       "|    word   |     tfidf      |\n",
       "+-----------+----------------+\n",
       "| melbourne | 3.89143101194  |\n",
       "|  college  | 1.56136627032  |\n",
       "|   parade  | 5.51003183729  |\n",
       "| education |  2.4487155642  |\n",
       "|  teaches  |  3.7712554105  |\n",
       "| currently | 1.63708896913  |\n",
       "|   edflhe  | 10.9864953892  |\n",
       "|    also   | 0.462727091616 |\n",
       "|   coburg  |  7.8510011733  |\n",
       "|  coached  |  3.992562414   |\n",
       "+-----------+----------------+\n",
       "[10379283 rows x 2 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#type(tfidf)\n",
    "people[['tfidf']].stack('tfidf', new_column_name=['word','tfidf'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TF-IDF 점수가 높은 단어들이 훨씬 더 정보로서 가치가 높습니다. =rare word"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 유명인사들 간의 거리를 직접 계산해 보기\n",
    "\n",
    "몇몇 유명인사들의 문서들 간의 거리를 직접 계산해 봅시다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "먼저 'Bill Clinton'을 찾아서 **clinton**에 저장합시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "clinton = people[people['name'] == 'Bill Clinton']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "먼저 'David Beckham'을 찾아서 **beckham**에 저장합시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "beckham = people[people['name'] == 'David Beckham']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obama가 Clinton에 가까울까요? 아니면 Beckham에 더 가까을까요?\n",
    "\n",
    "cosine 거리를 사용하겠습니다. 이는 아래식으로 표현됩니다.\n",
    "\n",
    "    distance = 1 - cosine_similarity\n",
    "\n",
    "Obama 대통령의 문서가 유명한 축구선수인 David Beckham의 문서보다 Clinton 대통령의 문서에 가까운지 알아 보겠습니다.\n",
    "아래 메소드를 사용합니다.\n",
    "\n",
    "    graphlab.distances.cosine(문서1의tfidf, 문서2의tfidf)\n",
    "    \n",
    "주의: 이 메소드는 SArray가 아닌 dictionary 또는 list을 인자로 받습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "먼저 obama와 clinton 간의 거리를 확인하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8339854936884276"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graphlab.distances.cosine(obama[0]['tfidf'], clinton[0]['tfidf'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "그 다음 obama와 beckham 간의 거리를 확인하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9791305844747478"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graphlab.distances.cosine(obama[0]['tfidf'], beckham[0]['tfidf'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "누가 더 obama에 가깝나요?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 문서 조회를 위해 최근접 이웃 (nearest neighbor) 모델 만들기\n",
    "\n",
    "이제 nearest neighbor 모델을 만들어서 문서 조회에 이용해 봅시다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "아래 메소드를 이용해서 nearest neighboer 모델을 만들고 **knn_model**에 저장하세요.\n",
    "\n",
    "    graphlab.nearest_neighbors.create(학습데이터, features=사용하고자하는컬럼의리스트, label=각행의구분자역할을할컬럼명)\n",
    "    \n",
    "여기서는 피쳐로 'tfidf'만을 사용하고 label로는 이름을 사용하겠습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting brute force nearest neighbors model training.</pre>"
      ],
      "text/plain": [
       "Starting brute force nearest neighbors model training."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "knn_model = graphlab.nearest_neighbors.create(people,features=['tfidf'],label='name',distance='cosine')\n",
    "#people['name']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 문서 조회에 nearest-neighbors 모델을 이용하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 누가 Obama에 가장 가까운가?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "아래 메소드를 이용해서 Obama에 가까운 인물들을 찾아 보세요.\n",
    "\n",
    "    model.query(SFrame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting pairwise querying.</pre>"
      ],
      "text/plain": [
       "Starting pairwise querying."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Query points | # Pairs | % Complete. | Elapsed Time |</pre>"
      ],
      "text/plain": [
       "| Query points | # Pairs | % Complete. | Elapsed Time |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
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    },
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       "<pre>| Done         |         | 100         | 728.299ms    |</pre>"
      ],
      "text/plain": [
       "| Done         |         | 100         | 728.299ms    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">query_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">reference_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">distance</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">rank</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Barack Obama</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Joe Biden</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.703138676734</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Samantha Power</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.742981902328</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Hillary Rodham Clinton</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.758358397887</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Eric Stern (politician)</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.770561227601</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[5 rows x 4 columns]<br/>\n",
       "</div>"
      ],
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       "Columns:\n",
       "\tquery_label\tint\n",
       "\treference_label\tstr\n",
       "\tdistance\tfloat\n",
       "\trank\tint\n",
       "\n",
       "Rows: 5\n",
       "\n",
       "Data:\n",
       "+-------------+-------------------------+----------------+------+\n",
       "| query_label |     reference_label     |    distance    | rank |\n",
       "+-------------+-------------------------+----------------+------+\n",
       "|      0      |       Barack Obama      |      0.0       |  1   |\n",
       "|      0      |        Joe Biden        | 0.703138676734 |  2   |\n",
       "|      0      |      Samantha Power     | 0.742981902328 |  3   |\n",
       "|      0      |  Hillary Rodham Clinton | 0.758358397887 |  4   |\n",
       "|      0      | Eric Stern (politician) | 0.770561227601 |  5   |\n",
       "+-------------+-------------------------+----------------+------+\n",
       "[5 rows x 4 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_model.query(obama)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Obama 대통령의 문서는 그의 부통령이었던 Biden과 가장 가깝고 그 다음으로는 Liberman과 같은 다른 정치인들이 등장하는 것을 확인할 수 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 다른 인물들로 문서 조회해 보기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'Taylor Swift'를 찾아서 **swift**에 저장해 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "swift = people[people['name'] == 'Taylor Swift']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Swift와 가까운 인물들을 찾아 봅시다.\n",
    "\n",
    "    model.query(SFrame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting pairwise querying.</pre>"
      ],
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       "Starting pairwise querying."
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     },
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    },
    {
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       "<pre>| Query points | # Pairs | % Complete. | Elapsed Time |</pre>"
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       "| Query points | # Pairs | % Complete. | Elapsed Time |"
      ]
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     "output_type": "display_data"
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    },
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">query_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">reference_label</th>\n",
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       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Taylor Swift</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Al Swift</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.699046316493</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Bill Swift</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.712560304479</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Ed Sheeran</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.735540453472</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Carrie Underwood</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.736410347487</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[5 rows x 4 columns]<br/>\n",
       "</div>"
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       "Columns:\n",
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       "\tdistance\tfloat\n",
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       "\n",
       "Rows: 5\n",
       "\n",
       "Data:\n",
       "+-------------+------------------+----------------+------+\n",
       "| query_label | reference_label  |    distance    | rank |\n",
       "+-------------+------------------+----------------+------+\n",
       "|      0      |   Taylor Swift   |      0.0       |  1   |\n",
       "|      0      |     Al Swift     | 0.699046316493 |  2   |\n",
       "|      0      |    Bill Swift    | 0.712560304479 |  3   |\n",
       "|      0      |    Ed Sheeran    | 0.735540453472 |  4   |\n",
       "|      0      | Carrie Underwood | 0.736410347487 |  5   |\n",
       "+-------------+------------------+----------------+------+\n",
       "[5 rows x 4 columns]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_model.query(swift)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "이번에는 'Angelina Jolie'를 찾아서 **jolie**에 저장합시다. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "jolie = people[people['name'] == 'Angelina Jolie']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "jolie와 가까운 인물들을 찾아 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting pairwise querying.</pre>"
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       "| Query points | # Pairs | % Complete. | Elapsed Time |"
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     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">query_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">reference_label</th>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Brad Pitt</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
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       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Keith Jolie</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.770688506797</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Julianne Moore</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.776274899793</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[5 rows x 4 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tquery_label\tint\n",
       "\treference_label\tstr\n",
       "\tdistance\tfloat\n",
       "\trank\tint\n",
       "\n",
       "Rows: 5\n",
       "\n",
       "Data:\n",
       "+-------------+-----------------+----------------+------+\n",
       "| query_label | reference_label |    distance    | rank |\n",
       "+-------------+-----------------+----------------+------+\n",
       "|      0      |  Angelina Jolie |      0.0       |  1   |\n",
       "|      0      |    Brad Pitt    | 0.730168606132 |  2   |\n",
       "|      0      | Barbara Hershey | 0.761752081266 |  3   |\n",
       "|      0      |   Keith Jolie   | 0.770688506797 |  4   |\n",
       "|      0      |  Julianne Moore | 0.776274899793 |  5   |\n",
       "+-------------+-----------------+----------------+------+\n",
       "[5 rows x 4 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_model.query(jolie)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'Arnold Schwarzenegger'는 어떨까요? 먼저 해당 문서를 찾아서 **arnold**에 저장하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "arnold = people[people['name'] == 'Arnold Schwarzenegger']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "이제 Arnold와 가까운 인물들을 찾아 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting pairwise querying.</pre>"
      ],
      "text/plain": [
       "Starting pairwise querying."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Query points | # Pairs | % Complete. | Elapsed Time |</pre>"
      ],
      "text/plain": [
       "| Query points | # Pairs | % Complete. | Elapsed Time |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 0            | 1       | 0.00169288  | 20.466ms     |</pre>"
      ],
      "text/plain": [
       "| 0            | 1       | 0.00169288  | 20.466ms     |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Done         |         | 100         | 838.704ms    |</pre>"
      ],
      "text/plain": [
       "| Done         |         | 100         | 838.704ms    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">query_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">reference_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">distance</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">rank</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Arnold Schwarzenegger</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Bonnie Garcia</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.79194972794</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Paul Grant (bodybuilder)</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.803523487381</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">James Tramel</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.830161679751</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Gray Davis</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.838121872529</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[5 rows x 4 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tquery_label\tint\n",
       "\treference_label\tstr\n",
       "\tdistance\tfloat\n",
       "\trank\tint\n",
       "\n",
       "Rows: 5\n",
       "\n",
       "Data:\n",
       "+-------------+--------------------------+----------------+------+\n",
       "| query_label |     reference_label      |    distance    | rank |\n",
       "+-------------+--------------------------+----------------+------+\n",
       "|      0      |  Arnold Schwarzenegger   |      0.0       |  1   |\n",
       "|      0      |      Bonnie Garcia       | 0.79194972794  |  2   |\n",
       "|      0      | Paul Grant (bodybuilder) | 0.803523487381 |  3   |\n",
       "|      0      |       James Tramel       | 0.830161679751 |  4   |\n",
       "|      0      |        Gray Davis        | 0.838121872529 |  5   |\n",
       "+-------------+--------------------------+----------------+------+\n",
       "[5 rows x 4 columns]"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_model.query(arnold)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 생각해 볼 거리\n",
    "\n",
    "### 이 노트북에서는 왜 데이터를 split을 하지 않을까요?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quiz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 1 \n",
    "Elton John 문서에서 가장 많이 등장하는 단어들은 무엇인가요?\n",
    "\n",
    "- 'Elton John'의 문서를 찾아서 저장합니다.\n",
    "- 'word_count' 컬럼만으로 이루어진 SFrame을 만들고 stack 명령을 이용해서 'word'와 'count'로 분리하세요.\n",
    "- 해당 결과값을 'count'로 내림차순으로 소팅하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "john = people[people['name'] == 'Elton John']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------------------------------+------------+-------------------------------+\n",
      "|              URI              |    name    |              text             |\n",
      "+-------------------------------+------------+-------------------------------+\n",
      "| <http://dbpedia.org/resour... | Elton John | sir elton hercules john cb... |\n",
      "+-------------------------------+------------+-------------------------------+\n",
      "+-------------------------------+-------------------------------+\n",
      "|           word_count          |             tfidf             |\n",
      "+-------------------------------+-------------------------------+\n",
      "| {'all': 1, 'least': 1, 'pr... | {'all': 1.6431112434912472... |\n",
      "+-------------------------------+-------------------------------+\n",
      "[? rows x 5 columns]\n",
      "Note: Only the head of the SFrame is printed. This SFrame is lazily evaluated.\n",
      "You can use sf.materialize() to force materialization.\n"
     ]
    }
   ],
   "source": [
    "print john"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "john_word_count_table = john[['word_count']].stack('word_count', new_column_name=['word', 'count'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------+-------+\n",
      "|   word   | count |\n",
      "+----------+-------+\n",
      "|  social  |   1   |\n",
      "| champion |   1   |\n",
      "|    be    |   1   |\n",
      "|   2014   |   1   |\n",
      "|  legal   |   1   |\n",
      "|  became  |   1   |\n",
      "|   2005   |   1   |\n",
      "| december |   2   |\n",
      "|    21    |   2   |\n",
      "| furnish  |   2   |\n",
      "+----------+-------+\n",
      "[255 rows x 2 columns]\n",
      "Note: Only the head of the SFrame is printed.\n",
      "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n"
     ]
    }
   ],
   "source": [
    "print john_word_count_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">word</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">the</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">in</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">and</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">of</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">a</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">has</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">john</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">he</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">on</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">award</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[255 rows x 2 columns]<br/>Note: Only the head of the SFrame is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tword\tstr\n",
       "\tcount\tint\n",
       "\n",
       "Rows: 255\n",
       "\n",
       "Data:\n",
       "+-------+-------+\n",
       "|  word | count |\n",
       "+-------+-------+\n",
       "|  the  |   27  |\n",
       "|   in  |   18  |\n",
       "|  and  |   15  |\n",
       "|   of  |   13  |\n",
       "|   a   |   10  |\n",
       "|  has  |   9   |\n",
       "|  john |   7   |\n",
       "|   he  |   7   |\n",
       "|   on  |   6   |\n",
       "| award |   5   |\n",
       "+-------+-------+\n",
       "[255 rows x 2 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "john_word_count_table.sort('count', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 2\n",
    "Elton John 문서에서 가장 높은 TF-IDF 값을 가지는 단어들은 무엇인가요?\n",
    "\n",
    "- 'tfidf' 컬럼만으로 이루어진 SFrame을 만들고 stack 명령을 이용해서 'word'와 'tfidf'로 분리하세요.\n",
    "- 해당 결과값을 'tfidf'로 내림차순으로 소팅하세요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "john_tfidf_table = john[['tfidf']].stack('tfidf', new_column_name=['word','tfidf'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">word</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">tfidf</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">furnish</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">18.38947184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">elton</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">17.48232027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">billboard</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">17.3036809575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">john</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">13.9393127924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">songwriters</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">11.250406447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">tonightcandle</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10.9864953892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">overallelton</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10.9864953892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">19702000</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10.2933482087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">fivedecade</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10.2933482087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">aids</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10.262846934</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[255 rows x 2 columns]<br/>Note: Only the head of the SFrame is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tword\tstr\n",
       "\ttfidf\tfloat\n",
       "\n",
       "Rows: 255\n",
       "\n",
       "Data:\n",
       "+---------------+---------------+\n",
       "|      word     |     tfidf     |\n",
       "+---------------+---------------+\n",
       "|    furnish    |  18.38947184  |\n",
       "|     elton     |  17.48232027  |\n",
       "|   billboard   | 17.3036809575 |\n",
       "|      john     | 13.9393127924 |\n",
       "|  songwriters  |  11.250406447 |\n",
       "| tonightcandle | 10.9864953892 |\n",
       "|  overallelton | 10.9864953892 |\n",
       "|    19702000   | 10.2933482087 |\n",
       "|   fivedecade  | 10.2933482087 |\n",
       "|      aids     |  10.262846934 |\n",
       "+---------------+---------------+\n",
       "[255 rows x 2 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "john_tfidf_table.sort('tfidf', ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 3\n",
    "\n",
    "Eltion John과 Victoria Beckham의 문서 간에 TF-IDF로 표현된 거리는 어느 정도일까요?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "vbeckham = people[people['name'] == 'Victoria Beckham']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">URI</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">name</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">text</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">word_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">&lt;http://dbpedia.org/resou<br>rce/Victoria_Beckham&gt; ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Victoria Beckham</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">victoria caroline beckham<br>ne adams born 17 april ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">{'millionin': 1,<br>'saying': 1, 'cameo': 1, ...</td>\n",
       "    </tr>\n",
       "</table>\n",
       "<table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">tfidf</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">{'millionin':<br>7.728398851203712, ...</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[1 rows x 5 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tURI\tstr\n",
       "\tname\tstr\n",
       "\ttext\tstr\n",
       "\tword_count\tdict\n",
       "\ttfidf\tdict\n",
       "\n",
       "Rows: 1\n",
       "\n",
       "Data:\n",
       "+-------------------------------+------------------+\n",
       "|              URI              |       name       |\n",
       "+-------------------------------+------------------+\n",
       "| <http://dbpedia.org/resour... | Victoria Beckham |\n",
       "+-------------------------------+------------------+\n",
       "+-------------------------------+-------------------------------+\n",
       "|              text             |           word_count          |\n",
       "+-------------------------------+-------------------------------+\n",
       "| victoria caroline beckham ... | {'millionin': 1, 'saying':... |\n",
       "+-------------------------------+-------------------------------+\n",
       "+-------------------------------+\n",
       "|             tfidf             |\n",
       "+-------------------------------+\n",
       "| {'millionin': 7.7283988512... |\n",
       "+-------------------------------+\n",
       "[1 rows x 5 columns]"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vbeckham.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">URI</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">name</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">text</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">word_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">&lt;http://dbpedia.org/resou<br>rce/Elton_John&gt; ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Elton John</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">sir elton hercules john<br>cbe born reginald ken ...</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">{'all': 1, 'least': 1,<br>'producer': 1, 'heavi ...</td>\n",
       "    </tr>\n",
       "</table>\n",
       "<table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">tfidf</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">{'all':<br>1.6431112434912472, ...</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[1 rows x 5 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tURI\tstr\n",
       "\tname\tstr\n",
       "\ttext\tstr\n",
       "\tword_count\tdict\n",
       "\ttfidf\tdict\n",
       "\n",
       "Rows: 1\n",
       "\n",
       "Data:\n",
       "+-------------------------------+------------+-------------------------------+\n",
       "|              URI              |    name    |              text             |\n",
       "+-------------------------------+------------+-------------------------------+\n",
       "| <http://dbpedia.org/resour... | Elton John | sir elton hercules john cb... |\n",
       "+-------------------------------+------------+-------------------------------+\n",
       "+-------------------------------+-------------------------------+\n",
       "|           word_count          |             tfidf             |\n",
       "+-------------------------------+-------------------------------+\n",
       "| {'all': 1, 'least': 1, 'pr... | {'all': 1.6431112434912472... |\n",
       "+-------------------------------+-------------------------------+\n",
       "[1 rows x 5 columns]"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "john.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9469446028990095"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graphlab.distances.cosine(john[0]['tfidf'], beckham[0]['tfidf'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 4\n",
    "\n",
    "Eltion John과 Paul McCartney의 문서 간에 TF-IDF로 표현된 거리는 어느 정도일까요?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "paul = people[people['name'] == 'Paul McCartney']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8250310029221779"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graphlab.distances.cosine(john[0]['tfidf'], paul[0]['tfidf'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 5\n",
    "\n",
    "Eltion John과 Paul McCartney가 가까울까요? 아니면 Victoria Beckham이 가까울까요?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Victoria Beckham"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 6\n",
    "\n",
    "word count를 이용해서 거리를 측정했을 때 Elton John에 가장 가까운 이웃은 누구일까요?\n",
    "- word_count를 이용한 nearest_neighbors 모델을 만든다.\n",
    "- query 메소드를 이용해서 최근접 이웃을 구한다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "참고: 위에서 만든 knn_model은 tf-idf를 이용해서 만들었기 때문에 word count를 이용해서 새로운 모델을 만들어야 합니다.\n",
    "\n",
    "    graphlab.nearest_neighbors.create(학습데이터, features=사용하고자하는컬럼의리스트, label=각행의구분자역할을할컬럼명)\n",
    "    \n",
    "label은 인물의 이름을 사용합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting brute force nearest neighbors model training.</pre>"
      ],
      "text/plain": [
       "Starting brute force nearest neighbors model training."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "knn_wc_model = graphlab.nearest_neighbors.create(people, features=['word_count'], label='name', distance='cosine')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting pairwise querying.</pre>"
      ],
      "text/plain": [
       "Starting pairwise querying."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Query points | # Pairs | % Complete. | Elapsed Time |</pre>"
      ],
      "text/plain": [
       "| Query points | # Pairs | % Complete. | Elapsed Time |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 0            | 1       | 0.00169288  | 15.78ms      |</pre>"
      ],
      "text/plain": [
       "| 0            | 1       | 0.00169288  | 15.78ms      |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Done         |         | 100         | 551.676ms    |</pre>"
      ],
      "text/plain": [
       "| Done         |         | 100         | 551.676ms    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">query_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">reference_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">distance</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">rank</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Elton John</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2.22044604925e-16</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Cliff Richard</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.16142415259</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Sandro Petrone</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.16822542751</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Rod Stewart</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.168327165587</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Malachi O'Doherty</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.177315545979</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[5 rows x 4 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tquery_label\tint\n",
       "\treference_label\tstr\n",
       "\tdistance\tfloat\n",
       "\trank\tint\n",
       "\n",
       "Rows: 5\n",
       "\n",
       "Data:\n",
       "+-------------+-------------------+-------------------+------+\n",
       "| query_label |  reference_label  |      distance     | rank |\n",
       "+-------------+-------------------+-------------------+------+\n",
       "|      0      |     Elton John    | 2.22044604925e-16 |  1   |\n",
       "|      0      |   Cliff Richard   |   0.16142415259   |  2   |\n",
       "|      0      |   Sandro Petrone  |   0.16822542751   |  3   |\n",
       "|      0      |    Rod Stewart    |   0.168327165587  |  4   |\n",
       "|      0      | Malachi O'Doherty |   0.177315545979  |  5   |\n",
       "+-------------+-------------------+-------------------+------+\n",
       "[5 rows x 4 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_wc_model.query(john)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 7 \n",
    "\n",
    "tf-idf를 이용해서 거리를 측정했을 때 Elton John과 가장 가까운 이웃은 누구인가요?\n",
    "- 위에서 사용한 knn_model을 이용하면 됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting pairwise querying.</pre>"
      ],
      "text/plain": [
       "Starting pairwise querying."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Query points | # Pairs | % Complete. | Elapsed Time |</pre>"
      ],
      "text/plain": [
       "| Query points | # Pairs | % Complete. | Elapsed Time |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| 0            | 1       | 0.00169288  | 22.216ms     |</pre>"
      ],
      "text/plain": [
       "| 0            | 1       | 0.00169288  | 22.216ms     |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Done         |         | 100         | 694.275ms    |</pre>"
      ],
      "text/plain": [
       "| Done         |         | 100         | 694.275ms    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">query_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">reference_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">distance</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">rank</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Elton John</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">-2.22044604925e-16</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Rod Stewart</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.717219667893</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">George Michael</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.747600998969</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Sting (musician)</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.747671954431</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Phil Collins</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.75119324879</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[5 rows x 4 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tquery_label\tint\n",
       "\treference_label\tstr\n",
       "\tdistance\tfloat\n",
       "\trank\tint\n",
       "\n",
       "Rows: 5\n",
       "\n",
       "Data:\n",
       "+-------------+------------------+--------------------+------+\n",
       "| query_label | reference_label  |      distance      | rank |\n",
       "+-------------+------------------+--------------------+------+\n",
       "|      0      |    Elton John    | -2.22044604925e-16 |  1   |\n",
       "|      0      |   Rod Stewart    |   0.717219667893   |  2   |\n",
       "|      0      |  George Michael  |   0.747600998969   |  3   |\n",
       "|      0      | Sting (musician) |   0.747671954431   |  4   |\n",
       "|      0      |   Phil Collins   |   0.75119324879    |  5   |\n",
       "+-------------+------------------+--------------------+------+\n",
       "[5 rows x 4 columns]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_model.query(john)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 8\n",
    "\n",
    "word count를 이용해서 거리를 측정했을 때 Victoria Beckham에 가장 가까운 이웃은 누구일까요?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting pairwise querying.</pre>"
      ],
      "text/plain": [
       "Starting pairwise querying."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
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      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Query points | # Pairs | % Complete. | Elapsed Time |</pre>"
      ],
      "text/plain": [
       "| Query points | # Pairs | % Complete. | Elapsed Time |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
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    },
    {
     "data": {
      "text/html": [
       "<pre>| 0            | 1       | 0.00169288  | 9.961ms      |</pre>"
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       "| 0            | 1       | 0.00169288  | 9.961ms      |"
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    {
     "data": {
      "text/html": [
       "<pre>| Done         |         | 100         | 479.193ms    |</pre>"
      ],
      "text/plain": [
       "| Done         |         | 100         | 479.193ms    |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
      ],
      "text/plain": [
       "+--------------+---------+-------------+--------------+"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">query_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">reference_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">distance</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">rank</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Victoria Beckham</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">-2.22044604925e-16</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Mary Fitzgerald (artist)</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.207307036115</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
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       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Adrienne Corri</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.214509782788</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Beverly Jane Fry</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.217466468741</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Raman Mundair</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.217695474992</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[5 rows x 4 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
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       "\treference_label\tstr\n",
       "\tdistance\tfloat\n",
       "\trank\tint\n",
       "\n",
       "Rows: 5\n",
       "\n",
       "Data:\n",
       "+-------------+--------------------------+--------------------+------+\n",
       "| query_label |     reference_label      |      distance      | rank |\n",
       "+-------------+--------------------------+--------------------+------+\n",
       "|      0      |     Victoria Beckham     | -2.22044604925e-16 |  1   |\n",
       "|      0      | Mary Fitzgerald (artist) |   0.207307036115   |  2   |\n",
       "|      0      |      Adrienne Corri      |   0.214509782788   |  3   |\n",
       "|      0      |     Beverly Jane Fry     |   0.217466468741   |  4   |\n",
       "|      0      |      Raman Mundair       |   0.217695474992   |  5   |\n",
       "+-------------+--------------------------+--------------------+------+\n",
       "[5 rows x 4 columns]"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_wc_model.query(vbeckham)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 9 \n",
    "\n",
    "tf-idf를 이용해서 거리를 측정했을 때 Victoria Beckham과 가장 가까운 이웃은 누구인가요?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>Starting pairwise querying.</pre>"
      ],
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       "Starting pairwise querying."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
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      "text/plain": [
       "+--------------+---------+-------------+--------------+"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>| Query points | # Pairs | % Complete. | Elapsed Time |</pre>"
      ],
      "text/plain": [
       "| Query points | # Pairs | % Complete. | Elapsed Time |"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
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      "text/plain": [
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       "<pre>| 0            | 1       | 0.00169288  | 19.678ms     |</pre>"
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       "<pre>| Done         |         | 100         | 701.173ms    |</pre>"
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       "| Done         |         | 100         | 701.173ms    |"
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    {
     "data": {
      "text/html": [
       "<pre>+--------------+---------+-------------+--------------+</pre>"
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      "text/plain": [
       "+--------------+---------+-------------+--------------+"
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    },
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     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
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       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">query_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">reference_label</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">distance</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Victoria Beckham</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1.11022302463e-16</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">David Beckham</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.548169610263</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
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       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Stephen Dow Beckham</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.784986706828</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Mel B</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.809585523409</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Caroline Rush</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0.819826422919</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">5</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[5 rows x 4 columns]<br/>\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tquery_label\tint\n",
       "\treference_label\tstr\n",
       "\tdistance\tfloat\n",
       "\trank\tint\n",
       "\n",
       "Rows: 5\n",
       "\n",
       "Data:\n",
       "+-------------+---------------------+-------------------+------+\n",
       "| query_label |   reference_label   |      distance     | rank |\n",
       "+-------------+---------------------+-------------------+------+\n",
       "|      0      |   Victoria Beckham  | 1.11022302463e-16 |  1   |\n",
       "|      0      |    David Beckham    |   0.548169610263  |  2   |\n",
       "|      0      | Stephen Dow Beckham |   0.784986706828  |  3   |\n",
       "|      0      |        Mel B        |   0.809585523409  |  4   |\n",
       "|      0      |    Caroline Rush    |   0.819826422919  |  5   |\n",
       "+-------------+---------------------+-------------------+------+\n",
       "[5 rows x 4 columns]"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn_model.query(vbeckham)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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