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Hashtag Recommendation with Attention-Based Neural Image Hashtagging Network

  • Gaosheng Wu
  • Yuhua Li
  • Wenjin Yan
  • Ruixuan Li
  • Xiwu Gu
  • Qi Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11302)

Abstract

With the increasing number of microblog users, the hashtag recommendation task has become an important component in social media. Most hashtag recommendation related methods get relative low precisions, because hashtags are not necessarily related to the content of tweets, which makes hashtag recommendation more challenging. In this work, we propose a new sequence-to-sequence method named attention based neural image hashtagging network (A-NIH) to model sequence relationship between social images and hashtags. To the best of our knowledge, this is the first work that applies attention mechanism to the image-only hashtag recommendation tasks. Our experimental results on the real-world social image dataset shows that our model performs better than the state-of-the-art methods.

Keywords

Image hashtag recommendation Deep learning Attention mechanism 

Notes

Acknowledgments

The authors wish to thank the anonymous reviewers for their helpful comments, and we gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal GPU used for this research, what’s more, we feel thankful that authors can provide baseline models for us so that we can conduct the experiments smoothly. This work is supported by the National Key Research and Development Program of China under grants 2016QY01W0202 and 2016YFB0800402, National Natural Science Foundation of China under grants 61572221, U1401258, 61433006, 61772219 and 61502185, Major Projects of the National Social Science Foundation under grant 16ZDA092, Science and Technology Support Program of Hubei Province under grant 2015AAA013, Science and Technology Program of Guangdong Province under grant 2014B010111007 and Guangxi High level innovation Team in Higher Education Institutions–Innovation Team of ASEAN Digital Cloud Big Data Security and Mining Technology.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Gaosheng Wu
    • 1
  • Yuhua Li
    • 1
  • Wenjin Yan
    • 1
  • Ruixuan Li
    • 1
  • Xiwu Gu
    • 1
  • Qi Yang
    • 1
  1. 1.School of Computer Science and TechnologyHuazhong University of Science and TecnnologyWuhanChina

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