2018/01/30 by Nikos Bikakis, Bikakis, Nikos, Vana Kalogeraki +3
Computer Science · #03F20 #11Y16 #65Y20 #68P05 #68P15 #68Q25 #68W25 #68W40 #97R50 #Computational Complexity (cs.CC) #Data Structures and Algorithms (cs.DS) #Databases (cs.DB) #E.1 #F.2 #FOS: Computer and information sciences #G.1.2 #G.2 #H.2.8 #H.3.1 #J.1 #J.4 #acm:03F20 #acm:11Y16 #acm:65Y20 #acm:68P05 #acm:68P15 #acm:68Q25 #acm:68W25 #acm:68W40 #acm:97R50 #cs.CC #cs.DB #cs.DS #msc:03F20 #msc:11Y16 #msc:65Y20 #msc:68P05 #msc:68P15 #msc:68Q25 #msc:68W25 #msc:68W40 #msc:97R50
paper · pdf · doi:10.48550/arxiv.1801.09973
This paper appears in 34th IEEE International Conference on Data Engineering (ICDE 2018)
arxiv created 2018/03/06 · arxiv updated 2018/03/08
A major challenge for social event organizers (e.g., event planning and marketing companies, venues) is attracting the maximum number of participants, since it has great impact on the success of the event, and, consequently, the expected gains (e.g., revenue, artist/brand publicity). In this paper, we introduce the Social Event Scheduling (SES) problem, which schedules a set of social events considering user preferences and behavior, events' spatiotemporal conflicts, and competing vents, in order to maximize the overall number of attendees. We show that SES is strongly NP-hard, even in highly restricted instances. To cope with the hardness of the SES problem we design a greedy approximation algorithm. Finally, we evaluate our method experimentally using a dataset from the Meetup event-based social network.