基于用户兴趣迁移的网络图书推荐模型研究

Research on Online Book Recommendation Model Based on User Interest Migration

在线图书推荐系统由于长期精准的推荐有可能导致用户得到一些重复推荐项目,不利于用户开拓视野。文章尝试在用户原有兴趣的基础上找到一种兴趣迁移的方法,使网络图书推荐呈现多样化。提出一种融合信息距离的语义相似度计算方法,实现语义相似度的扩散,从而有效引导用户兴趣的迁移,为网络用户提供多样性的图书推荐服务。设计实验验证了信息距离能够对推荐结果产生较大影响,融合信息量的语义相似度的网络图书推荐方法,可以给用户推荐其感兴趣并且更具有价值的项目。随着新项目的不断加入,项目的信息量也会动态变化,系统会不断调整推荐列表以适应用户需求。

The Iong-term over accurate recommendation of the online book recommendation system may lead to repeated recommendation items,and users5 horizon becomes increasingly narrow.This paper tries to find a method of interest migration on the basis of user's original interest,so as to diversify the recommendation of on line books.In this paper,a method of calculati ng sema ntic similarity based on information distance is proposed to realize the diffusion of semantic similarity,which can effectively guide the migration of users,in terests and provide a variety of book recomme ndati on services for n etwork users.This paper desig ns an experiment to verify that information distanee can have a greater impact on the recommendation results.The method of recomme ndatio n of on line books,which combi nes the sema ntic similarity of informatio n con tent,can recommend items of interest and value to users.With the continuous addition of new items,the information content of the projects will also change dynamically,and the system will constantly adjust the recommendation list to meet the needs of users.