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Semantic-Aware Techniques Enhanced Recommendations in Social Network

  • Jia-Yi Liao
  • Jia-Wei ChangEmail author
  • Chun-Yu Chang
  • Ying-Hung Pu
Conference paper
  • 7 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 551)

Abstract

This paper proposed the semantic-aware method to enhance the unknown but interesting recommendations. That is, the recommender system aims to suggest unknown but interesting groups to the target user, people should have the same interests or characteristics in the groups and the groups we recommended are high probably the target user like. The previous work, UBI, discovers unknown but interesting items based on the social behaviors of users. However, the work did not consider the information that the user really likes, e.g., the fan pages that user already joined. The information that user really likes is an important hint to recommend unknown but really interesting groups to the target user by merging social objects (such as fan pages and groups). We propose a semantic representation method of the social objects and integrate the semantic features into the UBI algorithm. Experimental results show that our method has better recommendations with unknown but user interesting items.

Keywords

Semantic-aware Recommender system Unknown but interesting 

References

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    Duan, J.-L., Prasad, S., Huang, J.-W.: Discovering unknown but interesting items in personal social network. In: Tan, P.-N., Chawla, S., Ho, C.-K., Bailey, J. (eds.) 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining. LNAI, vol. 7302, pp. 145–156. Springer, Heidelberg (2012)CrossRefGoogle Scholar
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    Chelmis, C., Prasanna, V.K.: Predicting communication intention in social networks. In: 2012 International Conference on Privacy, Security, Risk and Trust (PASSAT) and 2012 International Conference on Social Computing (SocialCom), pp. 184–194, IEEE, Amsterdam (2012)Google Scholar
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    CKIP Homepage. http://ckipsvr.iis.sinica.edu.tw/. Accessed 26 Mar 2019

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Jia-Yi Liao
    • 1
  • Jia-Wei Chang
    • 1
    Email author
  • Chun-Yu Chang
    • 2
  • Ying-Hung Pu
    • 3
  1. 1.National Taichung University of Science and TechnologyTaichung CityTaiwan
  2. 2.National Cheng Kung UniversityTainan CityTaiwan
  3. 3.Shu-Te UniversityKaohsiung CityTaiwan

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