A Tag Probability Correlation Based Microblog Recommendation Method

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• 关键词：Probability correlation ; Microblog recommendation ; User ; tag matrix ; Tag weight
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9948
• 期：1
• 页码：491-499
• 全文大小：475 KB
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• 作者单位：Di Zhang (19)
  Huifang Ma (19)
  Junjie Jia (19)
  Li Yu (19)
  
  19. College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China
  
• 丛书名：Neural Information Processing
• ISBN：978-3-319-46672-9
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9948

文摘

In order to improve users’ experience it is necessary to recommend valuable and interesting content for users. A tag probability correlation based microblog recommendation method (TPCMR) is presented via analyzing microblog features and the deficiencies of existing microblog recommendation algorithm. Firstly, our method takes advantage of the probability correlation between tags to construct the tag similarity matrix. Then the weight of the tag for each user is enhanced based on the relevance weighting scheme and the user tag matrix can be constructed. The matrix is updated using the tag similarity matrix, which contains both the user interest information and the relationship between tags and tags. Experimental results show that the algorithm is effective for microblog recommendation.