Journal of Computer Science and Technology

, Volume 33, Issue 4, pp 711–726 | Cite as

Hashtag Recommendation Based on Multi-Features of Microblogs

  • Fei-Fei Kou
  • Jun-Ping DuEmail author
  • Cong-Xian Yang
  • Yan-Song Shi
  • Wan-Qiu Cui
  • Mei-Yu Liang
  • Yue Geng
Regular Paper


Hashtag recommendation for microblogs is a very hot research topic that is useful to many applications involving microblogs. However, since short text in microblogs and low utilization rate of hashtags will lead to the data sparsity problem, it is difficult for typical hashtag recommendation methods to achieve accurate recommendation. In light of this, we propose HRMF, a hashtag recommendation method based on multi-features of microblogs in this article. First, our HRMF expands short text into long text, and then it simultaneously models multi-features (i.e., user, hashtag, text) of microblogs by designing a new topic model. To further alleviate the data sparsity problem, HRMF exploits hashtags of both similar users and similar microblogs as the candidate hashtags. In particular, to find similar users, HRMF combines the designed topic model with typical user-based collaborative filtering method. Finally, we realize hashtag recommendation by calculating the recommended score of each hashtag based on the generated topical representations of multi-features. Experimental results on a real-world dataset crawled from Sina Weibo demonstrate the effectiveness of our HRMF for hashtag recommendation.


hashtag recommendation topic model collaborative filtering method microblog 


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Fei-Fei Kou
    • 1
  • Jun-Ping Du
    • 1
    Email author
  • Cong-Xian Yang
    • 1
  • Yan-Song Shi
    • 1
  • Wan-Qiu Cui
    • 1
  • Mei-Yu Liang
    • 1
  • Yue Geng
    • 1
  1. 1.Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science Beijing University of Posts and TelecommunicationsBeijingChina

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