video-recommandation-mcp-server

Bilibili Video Recommendation System

An intelligent video recommendation system based on Analytic Hierarchy Process (AHP) that recommends high-quality video content through multi-criteria evaluation.

Features

• 🎯 Intelligent recommendation algorithm based on AHP (Analytic Hierarchy Process)
• 📊 Multi-dimensional video evaluation indicator system
• 🕷️ Bilibili video data crawling functionality
• 🔍 Intelligent video search and filtering
• 📈 Video data normalization processing
• 💾 Persistent storage of recommendation results

Main Modules

• ahp.py - Core AHP algorithm implementation
• spider.py - Bilibili video data crawler
• search.py - Video search functionality
• normalize_data.py - Data normalization processing
• video_operations.py - Video operation related functions
• server.py - Server-side implementation
• harry_mcp.py - MCP server implementation

Data Files

• bilibili_recommendations.csv - Bilibili recommended video data
• bilibili_recommendations_with_title.csv - Recommendation data with titles
• ahp_matrix.csv - AHP judgment matrix
• user_data.txt - User data
• bilibili_video_recommendations_list.txt - Recommended video list

Installation

pip install -r requirements.txt

Usage

1. Run the crawler to fetch video data
2. Configure the AHP judgment matrix
3. Execute the recommendation algorithm
4. View recommendation results

Technology Stack

• Python 3.x
• Pandas - Data processing
• NumPy - Numerical computation
• Requests - HTTP requests
• JSON - Data format

Contributing

Welcome to submit Issues and Pull Requests to improve the project!

License

MIT License