Personalized Tag Recommendation Based on User Preference and Content

被引：0
|
作者：
Shu, Zhaoxin [1 ]
Yu, Li [1 ]
Yang, Xiaoping [1 ]
机构：
[1] Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China
来源：
ADVANCED DATA MINING AND APPLICATIONS (ADMA 2010), PT II | 2010年 / 6441卷
关键词：
Tag Recommendation; Collaborative Tagging; Web2.0;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the widely use of collaborative tagging system nowadays, users could tag their favorite resources with free keywords. Tag recommendation technology is developed to help users in the process of tagging. However, most of the tag recommendation methods are merely based on the content of tagged resource. In this paper, it is argued that tags depend not only on the content of resource, but also on user preference. As such, a hybrid personalized tag recommendation method based on user preference and content is proposed. The experiment results show that the proposed method has advantages over traditional content-based methods.
引用
收藏
页码：348 / 355
页数：8
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