社会标签可以提供对象高度抽象的内容信息和个性偏好信息,因此标签的使用有助于提高个性推荐的精度.用户的偏好会随时间的变化而变化,网络中的资源也会随着时间推移而增加.如何根据用户兴趣的变化推荐出用户即时感兴趣的网络资源,已成为推荐系统研究的新问题.在用户-标签-对象三部分图网络结构中,结合标签使用频率和用户添加标签的时间,提出了一种利用标签时间加权的资源推荐算法.实验结果表明,利用标签时间加权的算法能有效地提高推荐的精度和多样性.%Social tags can provide highly abstract information about not only item contents but also personalized preferences, hence using labels could improve the accuracy of personalized recommendatioa As a result of user preferences changes over time,network resources also will be increased as time goes by. How to recommend the network resources in which users have immediate interest based on the user preferences changes becomes a new research problems in the recommendation system. Combined with using tag frequency and label time on user-object-tag tripartite graphs, we proposed a recommendation algorithm based on tag time-weighted network. Experimental results demonstrate that the usage of tag time-weighted can significantly improve accuracy and diversification of recommendations.
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