融合用户动态兴趣和社交信任的潜在好友推荐方法研究  

Potential Friend Recommendation Method Utilizing User Dynamic Interest and Social Trust

作　　者：谭春辉[1] 涂瑞德 TAN Chunhui;TU Ruide(School of Information Management,Central China Normal University,Wuhan 430079,China)

机构地区：[1]华中师范大学信息管理学院,湖北武汉430079

出　　处：《情报科学》2024年第9期1-8,共8页Information Science

基　　金：国家社会科学基金重点项目“有组织科研范式下哲学社会科学科研人员合作机制研究”(23ATQ007)

摘　　要：【目的/意义】针对现有潜在好友推荐方法在用户动态兴趣挖掘、信任分析方面的不足,提出了融合用户动态兴趣和社交信任的潜在好友推荐方法。【方法/过程】首先,利用潜在狄利克雷分配模型对用户已发布的博文进行主题分布学习,设计时间衰减函数进行加权,获取用户动态兴趣偏好特征并进行用户间兴趣偏好相似度计算;其次,利用社交网络结构特征进行全局信任度计算,利用用户社交行为特征进行局部信任度计算,线性加权得到最终的社交信任度;最后,融合用户兴趣偏好相似度和社交信任度进行目标用户潜在好友推荐,生成潜在好友推荐列表。【结果/结论】基于新浪微博数据集的实验结果表明,所提出的方法在推荐精度和Top-K推荐能力方面明显优于现有代表性的推荐方法。【创新/局限】相比于现有方法,本文综合考虑用户动态兴趣和社交信任两个部分的信息进行目标用户潜在好友推荐。但存在参数调优不足,多对多、一对多的群体信任关系也需充分利用。【Purpose/significance】Aiming at the shortcomings of existing friend recommendation methods in user dynamic interest mining and trust analysis,a friend recommendation method combining user dynamic interest and social trust is proposed.【Method/process】Firstly,the latent dirichlet allocationmodel is used to learn the topic distribution of the user′s published blog posts,and the time decay function is designed to be weighted to mine the user′s dynamic interest preference characteristics and calculate the similarity of interest preference between users.Secondly,the social network structure features are used to calculate the global trust degree,and the user′s social behavior features are used to calculate the local trust degree,and the final social trust degree is obtained by linear weighting.Finally,the user′s interest preference similarity and social trust degree are fused to recommend potential friends of the target user and generate a potential friend recommendation list.【Result/conclusion】The experimental results based on Sina Weibo dataset show that the proposed method is superior to the existing representative recommendation methods in terms of recommendation accuracy and Top-K recommendation ability.【Innovation/limitation】Compared to existing method,this paper comprehensively considers the information of user dynamic interest and social trust to recommend potential friends of the target user.But there is insufficient parameter tuning,and many to many,one to many group trust relationships also need to be fully utilized.

关 键 词：潜在好友推荐 用户动态兴趣 社交信任关系 LDA模型 Top-K推荐 

分 类 号：G254.9[文化科学—图书馆学]