Research on the Prediction System of Event Attendance in an Event-Based Social Network

Abstract

In recent years, an event-based social network recommendation system has attracted more and more researchers’ attention. Most EBSN recommendation systems mainly focus on recommending events to users. However, in many daily activities, it is necessary to accurately estimate the number of event participants for EBSN event organizers. As an effective means to solve the problem of event attendance prediction, the EBSN event attendance prediction system needs to mine the context information in EBSN fully and use the information to alleviate the problems of data sparsity and cold start. It brings some new challenges to the research of EBSN event attendance prediction systems. According to user characteristics and context factors, the main task of the EBSN event attendance prediction system is to obtain accurate user preferences, adopt efficient prediction algorithms to improve prediction performance, and avoid losses. This paper summarizes the research progress of the EBSN event attendance prediction system in recent years. Firstly, this paper analyzes the recent research on event attendance prediction in EBSN; secondly, we summarize the role, significance, and challenges of EBSN event attendance prediction; third, we summarize the critical technologies of EBSN event attendance prediction; the contents include mining the contextual information that affects the user’s participation in the event, user preference acquisition, the method of event attendance prediction, the data set of event attendance prediction, the evaluation indicators of event attendance prediction, etc.; fourth, we look forward to the future development directions of event attendance prediction from six aspects: the methods of integrating contextual factors, the user preference acquisition methods, the prediction algorithms, the utility evaluation of event attendance prediction, the user information security, and privacy protection, and the cold start issues; finally, we conclude this paper.

Discovery of User Groups Densely Connecting Virtual and Physical Worlds in Event-Based Social Networks

“…The services provided by EBSN have attracted a large number of users and are increasingly favored by them. Typical EBSN platforms include Meetup, Plancast, Doubanevent, and more (Lan et al, 2022).…”

A Predictive Paradigm for Event Popularity in Event-Based Social Networks

“…Liu et al [1] had investigated Meetup and defined it as event-based social networks (EBSNs). Research problems of EBSNs have been defined by researchers, such as event recommendation [2], group recommendation [4] and activefriend recommendation [23], [24]. The problem of event attendees recommendation is expressed by selecting top N users who are likely to attend events.…”

“…Since one event is announced, this event's invitation is sent to users. There are a lot of works [2]- [4] about finding a list of users who are willing to attend this event. Recommending this event to users has been investigated by many researchers [5]- [7].…”