{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T07:27:08Z","timestamp":1757575628571},"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":[[2021,8]]},"abstract":"<jats:p>Location prediction is of great importance in location-based applications for the construction of the smart city. To our knowledge, existing models for location prediction focus on the users' preference on POIs from the perspective of the human side. However, modeling users' interests from the historical trajectory is still limited by the data sparsity. Additionally, most of existing methods predict the next location according to the individual data independently. But the data sparsity makes it difficult to mine explicit mobility patterns or capture the casual behavior for each user. To address the issues above, we propose a novel Bi-direction Speculation and Dual-level Association method (BSDA), which considers both users' interests in POIs and POIs' appeal to users. Furthermore, we develop the cross-user and cross-POI association to alleviate the data sparsity by similar users and POIs to enrich the candidates. Experimental results on two public datasets demonstrate that BSDA achieves significant improvements over state-of-the-art methods.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/74","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"529-536","source":"Crossref","is-referenced-by-count":6,"title":["Location Predicts You: Location Prediction via Bi-direction Speculation and Dual-level Association"],"prefix":"10.24963","author":[{"given":"Xixi","family":"Li","sequence":"first","affiliation":[{"name":"National Engineering Research Center for Multimedia Software (NERCMS), School of Computer Science, Wuhan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruimin","family":"Hu","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Multimedia Software (NERCMS), School of Computer Science, Wuhan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Research Institute for an Inclusive Society through Engineering (RIISE), The University of Tokyo"},{"name":"Department of Information and Communication Engineering, The University of Tokyo"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Toshihiko","family":"Yamasaki","sequence":"additional","affiliation":[{"name":"Research Institute for an Inclusive Society through Engineering (RIISE), The University of Tokyo"},{"name":"Department of Information and Communication Engineering, The University of Tokyo"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2021","name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","start":{"date-parts":[[2021,8,19]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:01:14Z","timestamp":1628679674000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/74"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/74","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}