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电影推荐系统Demo

根据视频教程:基于知识图谱电影推荐问答系统实战_哔哩哔哩_bilibili

手撸了一个,简单的Demo,学习一下 Python 和 Neo4j 的简单使用。

环境

  • python3.7
  • neo4j-3.5.6
  • PyChram 2021

数据集

文件结构

如下图所示:

文件结构

说明:

  • datasets:存放数据集的文件夹(其中 Netflix数据集 过大没有上传)
  • datasets_out:存放数据预处理结果的文件夹,也就是运行 pre_process.py 后输出的结果文件
  • main.py:推荐模块
  • pre_process.py:数据预处理模块

运行过程

  1. 目前预处理的数据已经放入 datasets_out 文件夹中,想要自己再重新跑一遍就先运行一下 pre_process.py
  2. datasets_out 文件夹中的文件复制到 neo4j 安装目录下的 import 文件夹内
  3. 修改 main.py 中 neo4j 数据库的用户名密码改为你自己的
  4. 运行 main.py ,会提示“是否需要重新加载知识图谱? 输入0或1: ” 如果是第一次运行,输入1,会将neo4j中的数据清空,如有别的数据请先备份。
  5. 此时会开始将数据集载入 neo4j 中,可能过程较慢
  6. 之后按照提示输入即可,例如用户ID为944的就会有数据。

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Contributors

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