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- W2955408898 abstract "The prosperity of Location-Based Social Networks (LBSNs) facilitates a promising focus on personalized POI recommendation. The check-in activity is a multiple criteria decision making process. In this paper, we devise a novel personalized POI recommendation system called Multiple Criteria Ensemble Recommendation System (MCERS) to integrate the effect of geographical influence, temporal influence and categorical influence in a unified way to model dynamic user preferences for context-aware query. Specifically, we propose an ELM-based ensemble strategy to provide a more sophisticated framework for integrating different criteria to improve the quality of POI recommendations. Extensive experiments on three real-world datasets show that MCERS achieves better performance than existing state-of-the-art methods." @default.
- W2955408898 created "2019-07-12" @default.
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- W2955408898 date "2019-06-30" @default.
- W2955408898 modified "2023-09-27" @default.
- W2955408898 title "An ELM-Based Ensemble Strategy for POI Recommendation" @default.
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- W2955408898 doi "https://doi.org/10.1007/978-3-030-23307-5_32" @default.
- W2955408898 hasPublicationYear "2019" @default.
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