Social Event Scheduling
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A major challenge for social event organizers (e.g., event planning 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 events, in order to maximize the overall number of participants. 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 real dataset.
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