Abstract
Location-based recommender systems (LBRS) suggest friends, events, and places considering information about geographical locations. These recommendations can be made to individuals but also to groups of users, which implies satisfying the group as a whole. In this work, we analyze different alternatives for POI group recommendations based on a multi-agent system consisting of negotiating agents that represent a group of users. The results obtained thus far indicate that our multi-agent approach outperforms traditional aggregation approaches, and that the usage of LBSN information helps to improve both the quality of the recommendations and the efficiency of the recommendation process.
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Acknowledgements
We thank CONICET PIP Project 112-201501-00030, ANPCyT project PICT 2016-2973, C. Ríos and C. Villavicencio for their support and their work.
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Schiaffino, S., Godoy, D., Pace, J.A.D., Demazeau, Y. (2020). A MAS-Based Approach for POI Group Recommendation in LBSN. In: Demazeau, Y., Holvoet, T., Corchado, J., Costantini, S. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection. PAAMS 2020. Lecture Notes in Computer Science(), vol 12092. Springer, Cham. https://doi.org/10.1007/978-3-030-49778-1_19
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