基于用户扩展兴趣的微博推荐方法
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摘要
为解决微博用户兴趣提取不准确的问题,提出一种基于用户扩展兴趣的微博推荐方法。该方法将用户个体兴趣与关联兴趣结合为用户扩展兴趣进行微博推荐。其中,用户个体兴趣从用户标签、发布微博及交互微博中提取;用户关联兴趣通过用户与其关注用户间的关注关系强度、交互频繁程度和个体兴趣相似度获取。最后,计算用户扩展兴趣与待推荐微博的相似度,对相似度降序排列产生推荐列表。实验结果表明,新方法较传统方法更具有效性和准确性。
In order to deal with the problem of extracting interest of microblog users inaccurately,this paper proposed a microblog recommendation method based on extended interest of users. This method combined individual interest and associated interest to represent extended interest for recommending microblogs. It extracted individual interest of users from their tags,posted microblogs and interacted microblogs. Then it got associated interest by the strength of following/followed links,interaction frequency and individual interest similarity between users and their followee. Finally,it calculated the similarity between extended interest of users and the microblogs to be recommended,generated the recommendation lists by descending the order of similarity. Experimental results show that the method is more effective and precise than the traditional methods.
In order to deal with the problem of extracting interest of microblog users inaccurately,this paper proposed a microblog recommendation method based on extended interest of users. This method combined individual interest and associated interest to represent extended interest for recommending microblogs. It extracted individual interest of users from their tags,posted microblogs and interacted microblogs. Then it got associated interest by the strength of following/followed links,interaction frequency and individual interest similarity between users and their followee. Finally,it calculated the similarity between extended interest of users and the microblogs to be recommended,generated the recommendation lists by descending the order of similarity. Experimental results show that the method is more effective and precise than the traditional methods.
引文
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[11]Zhu Peisong,Qian Tieyun,Zhong Ming,et al. Inferring users’gender from interests:a tag embedding approach[J]. Neural Information Processing,2016,9950:86-94.
[12]Liu Zhiyuan,Chen Xinxiong,Sun Maosong. Mining the interests of Chinese microblogs via keyword extraction[J]. Frontiers of Computer Science,2012,6(1):76-87.
[13]贾美惠子.基于标签的微博信息推荐技术研究[D].兰州:西北师范大学,2016.(Jia Meihuizi. Research on microblog recommendation based on tags[D]. Lanzhou:Northwest Normal University,2016.)
[2] Xu Yan,Zhou Meilin,Han Siyao. Feature representation for microblog followee recommendation in classification framework[C]//Proc of the 7th International Conference on Advanced Computational Intelligence. Piscataway,NJ:IEEE Press,2015:318-322.
[3] Zhang Junjie,Lei Yongmei. Improving content recommendation in social streams via interest model[J]. Computer and Information Science,2015,566(1):57-70.
[4]高明,金澈清,钱卫宁,等.面向微博系统的实时个性化推荐[J].计算机学报,2014,37(4):963-975.(Gao Ming,Jin Cheqing,Qian Weining,et al. Real-time and personalized recommendation on microblogging system[J]. Chinese Journal of Computers,2014,37(4):963-975.)
[5]王宁宁,鲁燃,王智昊,等.基于用户标签的微博推荐算法[J].计算机应用研究,2017,34(1):58-61.(Wang Ningning,Lu Ran,Wang Zhihao,et al. Microblog recommendation algorithm based on usrs’tag[J]. Application Research of Computers,2017,34(1):58-61.)
[6] Zhou Xianke,Wu Sai,Chun Chun,et al. Realtime recommendation for microblog[J]. Information Sciences,2014,279:301-325.
[7]赵玲,张静.微博用户行为研究的多维解析[J].情报资料工作,2013(5):65-70.(Zhao Ling,Zhang Jing. Multi-dimensional analysis of microblog behavior research[J]. Information and Documentation,2013(5):65-70.)
[8]谭晋秀,何跃.基于K-means文本聚类的新浪微博个性化博文推荐研究[J].情报科学,2016,34(4):74-79.(Tan Jinxiu,He Yue.Study on Sina microblog personalized recommendation based on K-means text clustering[J]. Information Science,2016,34(4):74-79.)
[9] Ma Huifang,Jia Meihuizi,Zhang Di,et al. Combining tag correlation and user social relation for microblog recommendation[J]. Information Sciences,2017,385(C):325-337.
[10]仲兆满,管燕,胡云,等.基于背景和内容的微博用户兴趣挖掘[J].软件学报,2017,28(2):278-291.(Zhong Zhaoman,Guan Yan,Hu Yun,et al. Mining user interest on microblog based on profile and content[J]. Journal of Software,2017,28(2):278-291.)
[11]Zhu Peisong,Qian Tieyun,Zhong Ming,et al. Inferring users’gender from interests:a tag embedding approach[J]. Neural Information Processing,2016,9950:86-94.
[12]Liu Zhiyuan,Chen Xinxiong,Sun Maosong. Mining the interests of Chinese microblogs via keyword extraction[J]. Frontiers of Computer Science,2012,6(1):76-87.
[13]贾美惠子.基于标签的微博信息推荐技术研究[D].兰州:西北师范大学,2016.(Jia Meihuizi. Research on microblog recommendation based on tags[D]. Lanzhou:Northwest Normal University,2016.)