结合微博关注特性的UF_AT模型用户兴趣挖掘研究

微博作为国内主流社交网站,信息量与日俱增。目前微博用户兴趣挖掘方法大多停留在研究用户浏览网页时点击行为、用户所发微博内容或所在社区等表象层面,尚未深入到微博用户使用特性层面。从用户微博内容出发,结合用户关注对象微博,提出一种改进作者主题模型UF_AT（users focus-author topic）。最后对真实数据进行实验得出,模型在用户兴趣主题以及主题词概率值上均高于AT模型,而且用户兴趣主题准确、全面,同时验证了UF_AT模型在挖掘用户兴趣中的有效性。...

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Bibliographic Details
Published in计算机应用研究 Vol. 32; no. 7; pp. 1982 - 1985
Main Author 王永贵 张旭 任俊阳 刘宪国
Format Journal Article
LanguageChinese
Published 辽宁工程技术大学软件学院,辽宁葫芦岛,125105%吉林省煤业集团有限公司,长春,130012 2015
Subjects
作者主题模型
兴趣挖掘
微博
用户关注特性
用户关注特性
微博
作者主题模型
兴趣挖掘
user focus features
author topic model
microblog
interest minning
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Summary:微博作为国内主流社交网站,信息量与日俱增。目前微博用户兴趣挖掘方法大多停留在研究用户浏览网页时点击行为、用户所发微博内容或所在社区等表象层面,尚未深入到微博用户使用特性层面。从用户微博内容出发,结合用户关注对象微博,提出一种改进作者主题模型UF_AT（users focus-author topic）。最后对真实数据进行实验得出,模型在用户兴趣主题以及主题词概率值上均高于AT模型,而且用户兴趣主题准确、全面,同时验证了UF_AT模型在挖掘用户兴趣中的有效性。
Bibliography:Mieroblog as a mainstream social networking sites, the information is increasing by the explosive growth. Currently the methods of mieroblog user interest mining most remain in the level such as appearance of the research Of clicking action when the user browsing websites, the microblog content user post or the community they belong, yet in-depth features to microblog user level. From the content of users posting , combined with the focused users＇ microblog, this paper proposed an improved AT model UF_AT. At last the experiments on the real data show that the probability values of user＇ interest topics and the words on the topics of the model are higher than the AT model, and the users＇ interest topics are accuracy, entirety and verify the effective of the UFAT model on mining user＇ interest.
51-1196/TP
microblog; user focus features ; author topic model ; interest minning
Wang Yonggui , Zhang Xu, Ren Junyang, Liu Xianguo （ 1. College of Software, Liaoning Technical University, Huludao Liaoning 125105, China; 2.
ISSN:1001-3695
DOI:10.3969/j.issn.1001-3695.2015.07.016