{"pk":21632,"title":"Dual Weighted Graph Convolutional Network for POI Recommendation","subtitle":null,"abstract":"In recent years, with the widespread popularity of location-based social network platforms, the data generated by users on social networks has grown exponentially. There has been a growing focus on the problem of POI (Point-of-Interest) recommendations. Unlike traditional sequence recommendation that primarily considers the temporal dimension, POI recommendation needs to account for the influence of geographical information to a large extent. However, previous works in the graph construction process often only consider the places users have visited, neglecting those they haven't been to. To address this, we propose a Dual Weighted Graph Convolutional Network for POI recommendation called DualPOI. Specifically, we first leverage graph neural networks and attention mechanisms to capture users' local trajectory preferences for visited POIs. A delicately designed spatiotemporal encoder is conducted to model users' local spatiotemporal preferences. Subsequently, using a dual graph convolutional approach, we transfer the user's local preference information to a global scope, thereby modeling novel preferences for unvisited locations. Extensive experiments on four real-world datasets validate the effectiveness of our proposed method in enhancing the accuracy of POI recommendations. Comprehensive ablation studies and parameter analysis further confirm the efficacy of the proposed modules.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Artificial Intelligence; Predictive Processing; Big data; Knowledge representation; Neural Networks"}],"section":"Papers with Poster Presentation","is_remote":true,"remote_url":"https://escholarship.org/uc/item/9x86w5pr","frozenauthors":[{"first_name":"Zhi","middle_name":"","last_name":"Liu","name_suffix":"","institution":"Zhejiang University of Technology","department":""},{"first_name":"Deju","middle_name":"","last_name":"Zhang","name_suffix":"","institution":"College of Computer Science and Technology, Zhejiang University of Technology","department":""},{"first_name":"Junhui","middle_name":"","last_name":"Deng","name_suffix":"","institution":"College of Computer Science and Technology","department":""},{"first_name":"Guojiang","middle_name":"","last_name":"Shen","name_suffix":"","institution":"Zhejiang University of Technology","department":""},{"first_name":"Xiangjie","middle_name":"","last_name":"Kong","name_suffix":"","institution":"Zhejiang University of Technology","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2024-01-01T12:00:00-06:00","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/21632/galley/11231/download/"},{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/21632/galley/14540/download/"},{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/21632/galley/22022/download/"}]}