Research On Event Arrangement Strategies For Groups In Event-based Social Networks

Event-based social networks(EBSN) provides an event-centric online platform where users can create,publish and organize social events.This platform allows users with same interests to interact online and offline.Unlike traditional social networks,EBSN is event-driven,and its users usually participate in events as a group.With the wide application of EBSN,the needs of users are also increasing.They are no longer satisfied with the traditional personalized event recommendation,but need a more organized event participation scheduling service that is more in line with personal needs(such as budget,free time).In addition,the existing research only considers the interests of users,but not the interests of event organizers who are important components in EBSN.Existing research usually assumes that the information of users and events will remain unchanged once given,without considering the impact of changing information of users and events.Therefore,this paper focuses on the problems of "event sequence arrangement for groups" and "dynamic global group-event arrangement".Aiming at the event sequence arrangement for groups,this paper proposes a regret-aware event sequence arrangement strategy for groups.The strategy not only considers realistic constraints such as the free time period and the cost budget of the group members,the capacity of events,and the space-time conflict between events,but also emotional needs of the group for the category diversity and time balance of the event sequence arrangement.Considering these factors,the problem of the event sequence arrangement for groups is NP-hard,which brings great challenges to solve the problem.To solve the problem of the event sequence arrangement for groups,this paper firstly defines the problem and its related concepts formally,and proves that the problem is NP-hard.Then,in order to solve the problem effectively,this paper proposes a greedy-based heuristic algorithm.To further improve the performance and efficiency of the algorithm,this paper proposes three differential evolution-based meta-heuristic algorithms.Finally,we verify the effectiveness of the proposed algorithms through extensive experiments on real dataset,and the experimental results show that the performance of the proposed algorithms is better than that of the baseline algorithm.Aiming at the dynamic global group-event arrangement,this paper proposes a dynamic global group-event arrangement strategy considering constraints.The strategy not only considers the satisfaction of both groups and event organizers,but also the impact of the dynamic behavior(information changes)of groups and events.Firstly,this paper proposes the global group-event arrangement with constraints(GGEAC)problem and the dynamic global group event arrangement(DGGEA)problem.Then formally define the two problems,and prove that the GGEAC problem is NP-hard.In order to solve the GGEAC problem,this paper proposes a greedy strategy-based heuristic algorithm and an adjustment strategy-based two-dimensional dynamic programming algorithm.As for the DGGEA problem,this paper proposes four incremental adjustment algorithms to handle different dynamic information changes to adjust the original arrangement flexibly and effectively,thereby improving the efficiency and saving computing resources.Finally,we verify the effectiveness and efficiency of the proposed algorithms through extensive experiments on real dataset.