https://github.com/becky-dai/user-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation

User-based collaborative filtering algorithm and neo4j database for movie recommendation 基于用户的协同过滤算法和neo4j数据库的电影推荐
https://github.com/becky-dai/user-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation

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User-based collaborative filtering algorithm and neo4j database for movie recommendation 基于用户的协同过滤算法和neo4j数据库的电影推荐

• Host: GitHub
• URL: https://github.com/becky-dai/user-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation
• Owner: Becky-Dai
• Created: 2024-07-09T08:54:13.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-07-12T05:25:06.000Z (6 months ago)
• Last Synced: 2024-07-12T09:28:25.387Z (6 months ago)
• Language: Python
• Size: 9.61 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# User-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation

User-based collaborative filtering algorithm and neo4j database for movie recommendation (full-stack project)

基于用户的协同过滤算法和neo4j数据库的电影推荐全栈项目

# The 1st step : the data processing work

第一步是数据处理工作。

pre_process.py is the data processing file, and specific usage and comments are in this file.

pre_process.py是数据处理文件，具体的用法和注释都在这个文件里。

The original data is under datasets folder, I zip all the data and uploaded it as it is quite large. 

原数据在datasets文件夹下，由于数据比较大，我就zip所有数据上传了。

![image](https://github.com/Becky-Dai/User-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation/assets/58799631/3ac6abae-0299-49e0-8971-2fd807e6ca1d)

The processed data is under datasets_out.

处理后的数据在datasets_out下。

![image](https://github.com/Becky-Dai/User-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation/assets/58799631/4a468c96-85ec-4e84-987e-40a1777308b8)

The code to import the data into the neo4j database is in import import.docx. The database after import is shown below.

将数据导入neo4j数据库的代码在import导入.docx里面。导入之后的数据库如下所示。

![image](https://github.com/Becky-Dai/User-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation/assets/58799631/6e87b2e0-f84f-4761-8237-dd991cef8db7)

# The 2nd step : Computing on data with collaborative filtering algorithms

第二步是用协同过滤算法对数据进行计算

I'm using Django's framework, so I wrote all the specific code in pyneo_utils.py

我用的是Django的框架，所以我把具体的代码都写在了pyneo_utils.py里面

The exact usage and comments are clearly and detailed in pyneo_utils.py.

具体的用法和注释都被清楚且详细地写在了pyneo_utils.py里面。

# The 3rd step : Design the front end and connect the front and back ends

第三步设计前端和连接前后端

This is the home page of my front-end page.

这是我的前端网页的home page。

![image](https://github.com/Becky-Dai/User-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation/assets/58799631/7a6d2cff-c69a-487f-846d-6dfa8d9b50fa)

This is my movie recommendations page

这是我的推荐页面

![image](https://github.com/Becky-Dai/User-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation/assets/58799631/b2ac04d8-0417-4850-83cb-d56a319274d1)

![image](https://github.com/Becky-Dai/User-based-collaborative-filtering-algorithm-and-neo4j-database-for-movie-recommendation/assets/58799631/ffbe040c-4c39-485e-b9ab-ab457741f489)

The most important code about this project has been shown in the appropriate folder, while the rest of the part about Django setup has been omitted, and the project can be basically restored based on these main codes. If you want to get the full code please contact: [email protected]

关于这个项目的最主要的代码已经在相应的文件夹下进行了展示，而其余的关于Django的设置部分就省略了，根据这些主要代码基本上可以还原这个项目。如果想获取全部的代码请联系：[email protected]