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Combining long-term and short-term user interest for personalized hashtag recommendation

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Abstract

Hashtags, terms prefixed by a hash-symbol #, are widely used and inserted anywhere within short messages (tweets) on micro-blogging systems as they present rich sentiment information on topics that people are interested in. In this paper, we focus on the problem of hashtag recommendation considering their personalized and temporal aspects. As far as we know, this is the first work addressing this issue specially to recommend personalized hashtags combining longterm and short-term user interest.We introduce three features to capture personal and temporal user interest: 1) hashtag textual information; 2) user behavior; and 3) time. We offer two recommendation models for comparison: a linearcombined model, and an enhanced session-based temporal graph (STG) model, Topic-STG, considering the features to learn user preferences and subsequently recommend personalized hashtags. Experiments on two real tweet datasets illustrate the effectiveness of the proposed models and algorithms.

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Author information

Authors and Affiliations

  1. Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100190, China

    Jianjun Yu

  2. State Key Lab of Software Development Environment, Beihang University, Beijing, 100190, China

    Tongyu Zhu

Authors
  1. Jianjun Yu
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  2. Tongyu Zhu
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Corresponding author

Correspondence to Tongyu Zhu.

Additional information

Jianjun Yu received his BS from Zhejiang University of Technology, China in 2002, and PhD from Beihang University, China in 2007. He is currently an associate researcher at Computer Network Information Center, Chinese Academy of Sciences, China. His research interests include data mining, cloud computing.

Tongyu Zhu received his BS from Tsinghua University, China in 1992, and PhD from Beihang University, China in 2010. He is currently an associate professor in the School of Computer Science and Engineering at Beihang University. His research interests include data mining, cloud computing, and transportation planning.

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Cite this article

Yu, J., Zhu, T. Combining long-term and short-term user interest for personalized hashtag recommendation. Front. Comput. Sci. 9, 608–622 (2015). https://doi.org/10.1007/s11704-015-4284-x

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  • DOI: https://doi.org/10.1007/s11704-015-4284-x

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