Abstract
Nowadays, we rely increasingly on mobile applications and social networking websites to organize group events and/or search events to participate. Most existing services and platforms focus on distributing event invitations based on user profiles thus neglecting the fact that event attendees can significantly affect each other’s degree of satisfaction. To address this issue, we propose a reinforcement learning based group event invitation algorithm that can track relationships of users and use response rate and post-event reviews as feedback to guide invitation receiver selection process. Experimental results indicate that our proposed algorithm achieves better performance in term of satisfaction and connectivity of users when k-core algorithm and greedy search algorithm are compared.
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Acknowledgement
This work is partially supported by the National Natural Science Foundation of China under Grant No.61977044, the Key R&D Program of Shaanxi Province under grant No.2020GY-221, 2020ZDLGY10-05, the Natural Science Basis Research Plan in Shaanxi Province of China under Grant No.2020JM-303, 2020JM-302), the Fundamental Research Funds for the Central Universities of China under Grant No.GK201903090.
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Ai, C., Zhong, W., Guo, L. (2020). Reinforcement Learning Based Group Event Invitation Algorithm. In: Yu, D., Dressler, F., Yu, J. (eds) Wireless Algorithms, Systems, and Applications. WASA 2020. Lecture Notes in Computer Science(), vol 12384. Springer, Cham. https://doi.org/10.1007/978-3-030-59016-1_1
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