BiSheServer

Overview

The BiSheServer project presents an intriguing movie recommendation system developed as part of an undergraduate thesis. Utilizing a robust technological stack including Django, MongoDB, MySQL, and Redis, this system effectively analyzes user behavior to generate personalized movie suggestions. By leveraging data scraped from Douban, the platform aims to enhance user engagement and satisfaction through tailored recommendations, making it an exciting exploration in the realm of big data and user interaction.

The system adopts the MTV (Model-Template-View) architectural pattern, ensuring a structured and efficient development process. Special attention has been paid to the user interface, enhanced using SimpleUI, which promises a polished and user-friendly experience for both developers and end-users. This project showcases a clever integration of various technologies and methodologies to address the increasingly popular domain of recommendation systems.

Features

• Django Framework: The project is built on Django, offering a robust backend solution that supports rapid development and scalability.
• User-Centric Recommendations: By utilizing user profiles and behavior logs, the system effectively generates tailored movie recommendations based on individual preferences.
• Multiple Database Support: Combines MongoDB, MySQL, and Redis for data storage, allowing efficient management and quick data retrieval.
• Data Processing with Hadoop and Spark: Harnesses the power of big data technologies to analyze and process large datasets, enhancing the recommendation quality.
• Intuitive Interface: The management system is enhanced with SimpleUI, providing a visually appealing and easy-to-navigate interface.
• Comprehensive Documentation: Detailed installation and usage instructions facilitate ease of setup and understanding for users and developers.
• Open Source License: Released under the Apache-2.0 License, promoting collaboration and improvement by the community.