基于背景和内容的微博用户兴趣挖掘  

Mining User Interests on Microblog Based on Profile and Content

作　　者：仲兆满[1,2] 管燕[1] 胡云[1] 李存华[1] 

机构地区：[1]淮海工学院计算机工程学院,江苏连云港222005 [2]江苏金鸽网络科技有限公司软件研发中心,江苏连云港222005

出　　处：《软件学报》2017年第2期278-291,共14页Journal of Software

基　　金：国家自然科学基金(61403156);江苏省科技厅产学研前瞻性联合研究基金(BY2015048-02)~~

摘　　要：微博用户兴趣挖掘是个性化推荐、社群划分的基础工作.在深入分析微博网络特点的基础上,给出了能够揭示微博网络多模性的描述模型,对面向微博网络的后续研究具有参考价值.根据微博网络的特点,提出了基于背景的用户静态兴趣表示及挖掘方法,以及基于微博的用户动态兴趣表示和挖掘方法.针对微博网络中缺少背景信息、发表微博很少的大量不活跃用户,提出了基于关注的用户兴趣挖掘方法.以新浪微博为例,选取了时尚、企业管理、教育、军事、文化这5个领域进行用户兴趣挖掘及相似度计算的实验分析和比较,结果表明,与主流的兴趣挖掘方法相比,该微博用户兴趣的表示和挖掘方法可以有效地改善微博用户兴趣挖掘的效果.Mining user interests on microblog is the basis for personalized recommendation and community classification. A descriptive model of microblog network is proposed based on the in-depth analysis over the characteristics of microblog in the work, revealing properties of multi-mode microblog. The representation and mining method of profile-based static user interests and microblog post-based dynamic user interests are proposed respectively according to the characteristics of microblog network. For mining inactive users with little profile and few microblog posts, a method of follower-based interest mining is proposed. In the case study of Sina microblog, users in fashion, business management, education, military and culture are selected for experimental analysis and comparison of interest mining and similarity calculation. Experimental results show that the proposed representation and mining method can effectively improve user interest mining comparing with other state-of-the-art methods.

关 键 词：微博网络 用户兴趣表示 用户静态兴趣 用户动态兴趣 用户兴趣挖掘 用户兴趣相似度计算 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]