Abstract
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.
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Acknowledgment
The work has been supported by the National Natural Science Foundation of China (NSFC) under Grant Nos. 61472069, 61402089, 61332006 and U1401256; and the Fundamental Research Funds for the Central Universities under Grant Nos. N161602003 and N171607010.
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Xin, J., Li, M., Xu, W., Cai, Y., Lu, M., Wang, Z. (2018). Efficient Complex Social Event-Participant Planning Based on Heuristic Dynamic Programming. In: Pei, J., Manolopoulos, Y., Sadiq, S., Li, J. (eds) Database Systems for Advanced Applications. DASFAA 2018. Lecture Notes in Computer Science(), vol 10828. Springer, Cham. https://doi.org/10.1007/978-3-319-91458-9_16
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