{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T21:43:30Z","timestamp":1773956610006,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>Learning the embeddings for urban regions from human mobility data can reveal the functionality of regions, and then enables the correlated but distinct tasks such as crime prediction. Human mobility data contains rich but abundant information, which yields to the comprehensive region embeddings for cross domain tasks. In this paper, we propose multi-graph fusion networks (MGFN) to enable the cross domain prediction tasks. First, we integrate the graphs with spatio-temporal similarity as mobility patterns through a mobility graph fusion module. Then, in the mobility pattern joint learning module, we design the multi-level cross-attention mechanism to learn the comprehensive embeddings from multiple mobility patterns based on intra-pattern and inter-pattern messages. Finally, we conduct extensive experiments on real-world urban datasets. Experimental results demonstrate that the proposed MGFN outperforms the state-of-the-art methods by up to 12.35% improvement. https:\/\/github.com\/wushangbin\/MGFN<\/jats:p>","DOI":"10.24963\/ijcai.2022\/321","type":"proceedings-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T02:55:56Z","timestamp":1657940156000},"page":"2312-2318","source":"Crossref","is-referenced-by-count":37,"title":["Multi-Graph Fusion Networks for Urban Region Embedding"],"prefix":"10.24963","author":[{"given":"Shangbin","family":"Wu","sequence":"first","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Department of Computer Science and Technology, Xiamen University, China"}]},{"given":"Xu","family":"Yan","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Department of Computer Science and Technology, Xiamen University, China"}]},{"given":"Xiaoliang","family":"Fan","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Department of Computer Science and Technology, Xiamen University, China"}]},{"given":"Shirui","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Data Science and AI, Faculty of Information Technology, Monash University, Australia"}]},{"given":"Shichao","family":"Zhu","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences, China"},{"name":"School of Cyber Security, University of Chinese Academy of Sciences, China"}]},{"given":"Chuanpan","family":"Zheng","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Department of Computer Science and Technology, Xiamen University, China"}]},{"given":"Ming","family":"Cheng","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Department of Computer Science and Technology, Xiamen University, China"}]},{"given":"Cheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Department of Computer Science and Technology, Xiamen University, China"}]}],"member":"10584","event":{"name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","theme":"Artificial Intelligence","location":"Vienna, Austria","acronym":"IJCAI-2022","number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2022,7,23]]},"end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T11:09:02Z","timestamp":1658142542000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/321"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/321","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}