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GRIP: A Group Recommender Based on Interactive Preference Model

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Abstract

Numerous applications of recommender systems can provide us a tool to understand users. A group recommender reflects the analysis of multiple users’ behavior, and aims to provide each user of the group with the things they involve according to users’ preferences. Currently, most of the existing group recommenders ignore the interaction among the users. However, in the course of group activities, the interactive preferences will dramatically affect the success of recommenders. The problem becomes even more challenging when some unknown preferences of users are partly influenced by other users in the group. An interaction-based method named GRIP (Group Recommender Based on Interactive Preference) is presented which can use group activity history information and recommender post-rating feedback mechanism to generate interactive preference parameters. To evaluate the performance of the proposed method, it is compared with traditional collaborative filtering on the MovieLens dataset. The results indicate the superiority of the GRIP recommender for multi-users regarding both validity and accuracy.

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Bo-Han Li, An-Man Zhang, Wei Zheng, Shuo Wan, Xiao-Lin Qin & Xue Li

  2. Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing, 210016, China

    Bo-Han Li

  3. Jiangsu Easymap Geographic Information Technology Corp., Ltd., Yangzhou, 225000, China

    Bo-Han Li

  4. School of Information Technology and Electrical Engineering, the University of Queensland, Brisbane, QLD 4072, Australia

    Xue Li

  5. Unmanned Aerial Vehicle Research Institute, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Hai-Lian Yin

Authors
  1. Bo-Han Li
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  2. An-Man Zhang
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  3. Wei Zheng
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  4. Shuo Wan
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  5. Xiao-Lin Qin
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  6. Xue Li
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  7. Hai-Lian Yin
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Correspondence to Hai-Lian Yin.

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Li, BH., Zhang, AM., Zheng, W. et al. GRIP: A Group Recommender Based on Interactive Preference Model. J. Comput. Sci. Technol. 33, 1039–1055 (2018). https://doi.org/10.1007/s11390-018-1846-z

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  • DOI: https://doi.org/10.1007/s11390-018-1846-z

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