北京航空航天大学学报 ›› 2010, Vol. 36 ›› Issue (2): 188-192.

• 论文 • 上一篇    下一篇

基于概念聚类的用户兴趣建模方法

刘永利, 欧阳元新, 闻 佳, 熊 璋   

  1. 北京航空航天大学 计算机学院, 北京 100191
  • 收稿日期:2008-12-27 出版日期:2010-02-28 发布日期:2010-09-13
  • 作者简介:刘永利(1980-),男,河南焦作人,博士生,yongli.buaa@gmail.com.
  • 基金资助:

    国家自然科学基金资助项目(60803120)

Approach to modeling user interests using conceptual clustering

Liu Yongli, Ouyang Yuanxin, Wen Jia, Xiong Zhang   

  1. School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2008-12-27 Online:2010-02-28 Published:2010-09-13

摘要: Internet资源的指数级增长促进了个性化服务的发展.针对传统的用户兴趣建模方法在准确率和增量处理能力方面的不足,提出了一种新的基于概念聚类的用户兴趣建模方法UIM2C2(User Interest Modeling Method based on Conceptual Clustering).该方法首先通过分析用户访问的历史文档构造后缀树结构,然后选择不同的相似度阈值,以不同的粒度合并基本簇.依据不同阈值条件下合并的基本簇之间的包含关系,生成用户的兴趣层次.UIM2C2方法是针对文档的一个增量式、无监督的概念学习方法,因此用户描述文件可以轻易的获取和更新.最后,通过数据集20NewsGroup上的实验验证了UIM2C2方法在兴趣预测方面的有效性.

Abstract: The exponential increase of internet resources accelerated the development of effective personalization techniques. A new method for modeling user interest, named UIM2C2 (user interest modeling method based on conceptual clustering) was presented. The method analyzed documents that each user ever browsed and created a suffix tree. According to different pair-wise base cluster similarity thresholds, base clusters could be merged in the range of different granularity. Combining with the inclusion relation between merged base clusters under different granularity, an interest hierarchy was generated. UIM2C2 carried out incremental, unsupervised concept learning over Web documents so that user profiles could be acquired and updated easily. Experimental results prove the effectiveness of the method in Web page recommendation.

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