Whether this participant will attract you to this event? Exploiting Participant Influence for Event Recommendation
Refereed conference paper presented and published in conference proceedings


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AbstractWhen a user is making a decision on whether to participate an event in Event-based Social Networks (EBSN), one of the common considerations is who have agreed to join this event. The reason is that existing participants of the event affect the decision of the user, to which we refer as participant influence. However, participant influence is not well studied by previous works. In this paper, we propose an event recommendation model which considers participant influence, exploiting the influence of existing participants, on the decisions of new participants. Specifically, we investigate participant influence in relation to several commonly used contextual aspects of the event based on Poisson factorization. We have conducted extensive experiments on some datasets extracted from a real-world EBSN. The results demonstrate that the consideration of participant influence can improve event recommendation.
All Author(s) ListYi Liao, Xinshi Lin, Wai Lam
Name of Conference2016 IEEE International Conference on Data Mining
Start Date of Conference12/12/2016
End Date of Conference15/12/2016
Place of ConferenceBarcelona
Country/Region of ConferenceSpain
Proceedings Title2016 IEEE 16th International Conference on Data Mining (ICDM)
Year2016
Month12
PublisherIEEE
Pages1035 - 1040
ISSN2374-8486
LanguagesEnglish-United States

Last updated on 2021-18-02 at 23:48