Hot-pizz - Pizza-Ordering-Chatbot

This is Chatbot implementing NLP by Python-NLTK.

Language

python

Prerequisite

• python-NLTK
• python-Flask
• HTML & CSS
• JavaScript

STEPS	DESCRIPTION
"Sentence Tokenization"	Sentence tokenizer breaks text paragraph into sentences.
"Word Tokenization"	Word tokenizer breaks text paragraph into words.
"Stemming"	stemming just removes the last few characters, often leading to incorrect meanings and spelling errors
"Lemmatization"	lemmatization considers the context and converts the word to its meaningful base form

import nltk
nltk.dowload()

Sentence Tokenization

sent_tokens  =  nltk.sent_tokenize(text)

Word Tokenization

sent_tokens  =  nltk.sent_tokenize(text)

Stemming and Lemmatization

lemmer = nltk.stem.WordNetLemmatizer()
def LemTokens(tokens):
	return [lemmer.lemmatize(token) for token in tokens]
remove_punct_dict = dict((ord(punct), None) for punct in string.punctuation)
def LemNormalize(text):
	return LemTokens(nltk.word_tokenize(text.lower().translate(remove_punct_dict)))

Feature Extraction

from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity

TfidfVec = TfidfVectorizer(tokenizer=LemNormalize, stop_words='english')
tfidf = TfidfVec.fit_transform(sent_tokens)
vals = cosine_similarity(tfidf[-1], tfidf)

MongoDB

MongoDB is an NOSQL database for ChatBot.All the order are stored in the Database

Application

hot-pizz Chatbot