基于隐性反馈的自适应推荐系统研究

介绍个性化自适应推荐系统的整体架构与设计方法。阐述用户兴趣模型的建立，包括对用户个性化信息的收集、精炼处理、模糊语意处理、解模糊化及满意度计算。引入模糊自适应共振理论网络进行项目聚类分析，并进行推荐处理，实现自适应推荐服务。实验结果表明，系统对用户兴趣判断比较准确，能及时掌握用户兴趣偏移，推荐效果良好，且基本稳定。

Research on Self-adaptive Recommendation System Based on Implicit Feedback

This paper introduces the structure of the personalized recommendation system and the design method. It states the process of establishing user interest model, including data collection and pretreatment, data refining, fuzzy linguistic processing, defuzzification, and satisfaction calculation. It analyses clustering items and processes, implements self-adaptive recommendation services based on the fuzzy adaptive resonance theory. Experimental results show that the system is stable and effective to predict users interest preferences and capture users excursion of interests.