基于用户行为的个性化推荐系统的设计与应用①

目前电子商务网站提供的推荐服务很难满足用户的个性化需求,协同过滤算法作为应用最成功的推荐算法,依然存在数据稀疏性、用户评分真实性等问题,制约着推荐系统的质量。设计和实现了一个基于用户行为的个性化商品推荐系统,主要采用前融合组合推荐策略,避免了单纯使用协同过滤算法的弱点。阐述了基于用户行为的个性化推荐系统的设计思想和实现过程,最终通过实验验证了本推荐系统具有良好的推荐效果。

Design and Application of Personalized Recommendation System Based on Users Behavior

It is difficult for the e-commerce system to meet users individual requirements.As one of the most successful algorithms,the Collaborative Filtering Algorithm still has problems like sparsity of data and lack of authenticity in user rating.Based on the related work,a recommendation algorithm based on users actions is designed and implemented.It avoids the weakness of collaborative filtering techniques.This paper describes the recommended system＇s ideas and the implementation process,and proves that the recommendation system performed well through experimtnts.