Enhancing group recommendation by incorporating social relationship interactions

Mike Gartrell, Xinyu Xing, Qin Lv, Aaron Beach, Richard Han, Shivakant Mishra, Karim Seada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

139 Scopus citations

Abstract

Group recommendation, which makes recommendations to a group of users instead of individuals, has become increasingly important in both the workspace and people's social activities, such as brainstorming sessions for coworkers and social TV for family members or friends. Group recommendation is a challenging problem due to the dynamics of group memberships and diversity of group members. Previous work focused mainly on the content interests of group members and ignored the social characteristics within a group, resulting in suboptimal group recommendation performance. In this work, we propose a group recommendation method that utilizes both social and content interests of group members. We study the key characteristics of groups and propose (1) a group consensus function that captures the social, expertise, and interest dissimilarity among multiple group members; and (2) a generic framework that automatically analyzes group characteristics and constructs the corresponding group consensus function. Detailed user studies of diverse groups demonstrate the effectiveness of the proposed techniques, and the importance of incorporating both social and content interests in group recommender systems.

Original languageEnglish (US)
Title of host publicationProceedings of the 16th ACM International Conference on Supporting Group Work, GROUP'10
Pages97-106
Number of pages10
DOIs
StatePublished - 2010
Event16th ACM International Conference on Supporting Group Work, GROUP'10 - Sanibel Island, FL, United States
Duration: Nov 7 2010Nov 10 2010

Publication series

NameProceedings of the 16th ACM International Conference on Supporting Group Work, GROUP'10

Other

Other16th ACM International Conference on Supporting Group Work, GROUP'10
CountryUnited States
CitySanibel Island, FL
Period11/7/1011/10/10

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems

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  • Cite this

    Gartrell, M., Xing, X., Lv, Q., Beach, A., Han, R., Mishra, S., & Seada, K. (2010). Enhancing group recommendation by incorporating social relationship interactions. In Proceedings of the 16th ACM International Conference on Supporting Group Work, GROUP'10 (pp. 97-106). (Proceedings of the 16th ACM International Conference on Supporting Group Work, GROUP'10). https://doi.org/10.1145/1880071.1880087