毕业设计 基于Python+Q-Learning的论文推荐系统设计+论文+源码+部署文档+全部数据资料（优秀项目）.zip

# Paper-Recommandation-Based-on-RL It's a simple program to implement Paper Recommandation Algorithmm base on the Q-learning. When writing my bachelor's thesis, I coded it to implement and test the the recommandation algorithm I designed. The Title of my thesis is Design of Paper Recommendation Algorithm Based on Q - learning. And the abstract is showing below: In recent years, with the rapid development of information technology, the number of papers published on the Internet has exploded. In order to conduct scientific research, scholars must learn from others by reading other people's papers and further develop them. Faced with many papers, how to effectively recommend papers has become a research hotspot. Previous paper recommendation algorithms mainly use content-based methods, user-based interests, collaborative filtering algorithms, and various hybrid algorithms derived from these algorithms. However, these algorithms have problems such as “data sparseness”, “cold start”, and “ignoring interest dynamics”. Inspired by the reinforcement learning recommendation algorithm of e-commerce platform, this paper designs a paper recommendation algorithm based on Q-Learning method in reinforcement learning to solve the above problems. The paper recommendation algorithm can dynamically update the recommendation weight according to the user's click on the paper to achieve a better recommendation effect. This paper uses the CiteULike dataset to conduct experiments and compares the recommended effects of the system with the traditional three paper recommendation algorithms. The results show that the proposed algorithm is better than the traditional paper recommendation algorithm. If you want to quote this program, please do the citation.