摘要
随着web信息爆炸增长,个性化信息服务成为人们研究的热点,用户兴趣建模是个性化服务的关键,针对当前用户建模的缺点和tag的广泛应用,对基于tag的用户兴趣建模进行研究,首先通过实验证明tag中蕴含用户稳定的兴趣及tag分布的其他特征,然后提出加权树形结构由粗到细的粒度表示用户模型,为提高服务时效性,对用户频繁一起使用的tag建立加权频繁项集表,该模型避免了提取关键词的复杂过程,而且从用户的角度表达用户的兴趣,实验表明该模型能提高个性化服务的质量。
With the explosive growth of web message, personalized information service becomes a focus for researchers, user interest model is a key technology in personalized service, this paper research tag-based User Modeling contrary to the shortcomings of the current user modeling and the extensive use of tag. Firstly, through some experiments prove that the tags which user using contains stable interest and other characteristics about tags distribution; then presents a weighted tree from coarse to fine granularity describes the user model. To improve the timeliness of service establish weighted frequent itemset table for often used together tags for each user. The model avoids the complex process of extracting key words and expresses user＇s interest from the user＇s point of view, experiments show that the model can improve the quality of personalized service.
出处
《计算机系统应用》
2011年第2期80-84,共5页
Computer Systems & Applications
关键词
TAG
用户建模
个性化服务
加权树
频繁项集
tag
user profile
personalized information
weighed tree
frequent itemset
