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movie_kg_demo

搭建一个小的电影知识图谱

我爬取了一个电影网站,得到了一千条电影的信息: enter description here 这个项目将描述如何使用这些电影数据搭建一个电影知识图谱,知识图谱中包含演员,电影,导演三种实体和参演,导演两种关系。

  1. 从电影信息中解析出实体和关系 直接运行get_data.py,会生成三种实体文件和两种关系文件,我放在了data文件夹下: enter description here

movie_entity.csv文件格式: enter description here movie2actor.csv文件格式: enter description here

  1. 导入neo4j数据库: 开启neo4j数据库,一词导入实体信息和关系信息:

导入实体信息:

load csv from "file:///actors_entity.csv" as line create (a:Actor{name:line[0]})
load csv from "file:///directors_entity.csv" as line create (d:Director{name:line[0]})
load csv from "file:///movie_entity.csv" as line create (m:Movie{name:line[0],country:line[1],language:line[2],pubdate:line[3],other_name:line[4],summary:line[5]})

导入关系信息:

load csv from "file:///movie2actor.csv" as line match (m:Movie{name:line[0]}),(a:Actor{name:line[1]}) merge (m)-[r:ActBy]->(a)
load csv from "file:///movie2director.csv" as line match (m:Movie{name:line[0]}),(d:Director{name:line[1]}) merge (m)-[r:DirectBy]->(d)

导入完成之后,就完成了知识图谱的构建,比方说,我们想看看周润发演过哪些电影:

match x=(:Movie)-[]->(a:Actor{name:'周润发'}) return x

结果我们找到: enter description here

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