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Social Network-Based Event Recommendation

  • Dinh Tuyen Hoang
  • Van Cuong Tran
  • Dosam Hwang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10448)

Abstract

The number of events generated on social networks has been growing quickly in recent years. It is difficult for users to find events that most suitably match their favorites. As a solution, the recommender system appears to solve this problem. However, event recommendation is significantly different from traditional recommendations, such as products and movies. Social events are created continuously, and only valid for a short time, so recommending a past event is meaningless. In this paper, we proposed a new even recommendation method based on social networks. First, the behavior of users be detected in order to build the user’s profile. Then the users’ relationship is extracted to measure the interaction strength between them. That is a fundamental factor affecting a decision of a user to attend events. In addition, the opinions about attended events are taken into account to evaluate the satisfaction of attendees by using deep learning method. Twitter is used as a case study for the method. The experiment shows that the method achieves promising results in comparison to other methods.

Keywords

Recommender system Event recommedation Social event 

Notes

Acknowledgment

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (21C000151).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Dinh Tuyen Hoang
    • 1
  • Van Cuong Tran
    • 2
  • Dosam Hwang
    • 1
  1. 1.Department of Computer EngineeringYeungnam UniversityGyeongsanSouth Korea
  2. 2.Quang Binh UniversityQuang BinhViet Nam

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