Efficient Complex Social Event-Participant Planning Based on Heuristic Dynamic Programming

To manage the Event Based Social Networks (EBSNs), an important task is to solve the Global Event Planning with Constraints (GEPC) problem, which arranges suitable social events to target users. Existing studies are not efficient enough because of the two-step framework. In this paper, we propose a more efficient method, called Heuristic-DP, which asynchronously considers all the constraints together. Using this method, we improve the computational complexity from \(O(|E|^2 + |U||E|^2)\) to O(|U||E|), where |U| is the number of users and |E| is the number of events in an EBSN platform. We also propose an improved heuristic strategy in one function of the heuristic-DP algorithm, which slightly increases the time cost, but can obtain a more accurate result. Finally, we verify the effectiveness and efficiency of our proposed algorithms through extensive experiments over real and synthetic datasets.