计算机科学 ›› 2012, Vol. 39 ›› Issue (8): 96-98.

• 计算机网络与信息安全 • 上一篇    下一篇

一种三部图网络中标签时间加权的推荐方法

顾亦然,陈敏   

  1. (南京邮电大学自动化学院 南京 210003)
  • 出版日期:2018-11-16 发布日期:2018-11-16

One Tag Time-weighted Recommend Approach on Tripartite Graphs Networks

  • Online:2018-11-16 Published:2018-11-16

摘要: 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。在用户一标签一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。

关键词: 个性化推荐,社会标签网络,时间加权,三部分网络

Abstract: Social tags can provide highly abstract information about not only item contents but also personalized prefe- rences,hence using labels could improve the accuracy of personalized recommendation. 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 frectuency and label time on user-object tag tripartite graphs,we pro- posed a recommendation algorithm based on tag timcweighted network. Experimental results dcxnonstrate that the usage of tag timcweighted can significantly improve accuracy and diversification of recommendations.

Key words: Personalized recommendation, Social tagging networks, Time-weighted, Tripartite graphs

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!