{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T10:39:20Z","timestamp":1768819160651,"version":"3.49.0"},"reference-count":55,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2021,11,29]],"date-time":"2021-11-29T00:00:00Z","timestamp":1638144000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Mutual Project of the Beijing Municipal Education Commission"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2022,10,31]]},"abstract":"<jats:p>POI recommendation has become an essential means to help people discover attractive places. Intuitively, activities have an important impact on users\u2019 decision-making, because users select POIs to attend corresponding activities. However, many existing studies ignore the social motivation of user behaviors and regard all check-ins as influenced only by individual user interests. As a result, they cannot model user preferences accurately, which degrades recommendation effectiveness. In this article, from the perspective of activities, this study proposes a probabilistic generative model called STARec. Specifically, based on the social effect of activities, STARec defines users\u2019 social preferences as distinct from their individual interests and combines these with individual user activity interests to effectively depict user preferences. Moreover, the inconsistency between users\u2019 social preferences and their decisions is modeled. An activity frequency feature is introduced to acquire accurate user social preferences because of close correlation between these and the key impact factor of corresponding check-ins. An alias sampling-based training method was used to accelerate training. Extensive experiments were conducted on two real-world datasets. Experimental results demonstrated that the proposed STARec model achieves superior performance in terms of high recommendation accuracy, robustness to data sparsity, effectiveness in handling cold-start problems, efficiency, and interpretability.<\/jats:p>","DOI":"10.1145\/3485631","type":"journal-article","created":{"date-parts":[[2021,11,29]],"date-time":"2021-11-29T21:00:38Z","timestamp":1638219638000},"page":"1-40","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":22,"title":["STARec: Adaptive Learning with Spatiotemporal and Activity Influence for POI Recommendation"],"prefix":"10.1145","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5696-0364","authenticated-orcid":false,"given":"Weiyu","family":"Ji","sequence":"first","affiliation":[{"name":"School of Computer Science (National Pilot Software Engineering School) &amp; Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2180-5986","authenticated-orcid":false,"given":"Xiangwu","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Computer Science (National Pilot Software Engineering School) &amp; Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1805-8342","authenticated-orcid":false,"given":"Yujie","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science (National Pilot Software Engineering School) &amp; Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Haidian District, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2021,11,29]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2903463"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3125620"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/2424321.2424348"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.5555\/944919.944937"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-012-9136-x"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411905"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3291060"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P15-1077"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2904066"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505637"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/2507157.2507182"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.5555\/3304889.3304985"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623756"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2906180"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00144"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/3057283"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403252"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/3183712"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487673"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403207"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2017.04.008"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","DOI":"10.1145\/3361217"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2020.102251"},{"key":"e_1_3_2_26_2","first-page":"1","volume-title":"Proceedings of the 14th Australasian Document Computing Symposium (ADCS\u201909)","author":"Newman David","year":"2009","unstructured":"David Newman, Sarvnaz Karimi, and Lawrence Cavedon. 2009. 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