{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T19:11:28Z","timestamp":1768590688480,"version":"3.49.0"},"reference-count":29,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,5,26]],"date-time":"2022-05-26T00:00:00Z","timestamp":1653523200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61806083"],"award-info":[{"award-number":["61806083"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872158"],"award-info":[{"award-number":["61872158"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172186"],"award-info":[{"award-number":["62172186"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["93K172021Z02"],"award-info":[{"award-number":["93K172021Z02"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities, JLU","award":["61806083"],"award-info":[{"award-number":["61806083"]}]},{"name":"Fundamental Research Funds for the Central Universities, JLU","award":["61872158"],"award-info":[{"award-number":["61872158"]}]},{"name":"Fundamental Research Funds for the Central Universities, JLU","award":["62172186"],"award-info":[{"award-number":["62172186"]}]},{"name":"Fundamental Research Funds for the Central Universities, JLU","award":["93K172021Z02"],"award-info":[{"award-number":["93K172021Z02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The next point-of-interest (POI) recommendation is one of the most essential applications in location-based social networks (LBSNs). Its main goal is to research the sequential patterns of user check-in activities and then predict a user\u2019s next destination. However, most previous studies have failed to make full use of spatio-temporal information to analyze user check-in periodic regularity, and some studies omit the user\u2019s transition preference for the category at the POI semantic level. These are important for analyzing the user\u2019s preference for check-in behavior. Long- and short-term preference modeling based on multi-level attention (LSMA) is put forward to solve the above problem and enhance the accuracy of the next POI recommendation. This can capture the user\u2019s long-term and short-term preferences separately, and consider the multi-faceted utilization of spatio-temporal information. In particular, it can analyze the periodic hobbies contained in the user\u2019s check-in. Moreover, a multi-level attention mechanism is designed to study the multi-factor dynamic representation of user check-in behavior and non-linear dependence between user check-ins, which can multi-angle and comprehensively explore a user\u2019s check-in interest. We also study the user\u2019s category transition preference at a coarse-grained semantic level to help construct the user\u2019s long-term and short-term preferences. Finally, experiments were carried out on two real-world datasets; the findings showed that LSMA modeling outperformed state-of-the-art recommendation systems.<\/jats:p>","DOI":"10.3390\/ijgi11060323","type":"journal-article","created":{"date-parts":[[2022,5,26]],"date-time":"2022-05-26T08:50:22Z","timestamp":1653555022000},"page":"323","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Long- and Short-Term Preference Modeling Based on Multi-Level Attention for Next POI Recommendation"],"prefix":"10.3390","volume":"11","author":[{"given":"Xueying","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Jilin University, Changchun 130012, China"}]},{"given":"Yanheng","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Jilin University, Changchun 130012, China"},{"name":"Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun 130012, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1890-7033","authenticated-orcid":false,"given":"Xu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun 130012, China"},{"name":"Center for Computer Fundamental Education, Jilin University, Changchun 130012, China"}]},{"given":"Zhaoqi","family":"Leng","sequence":"additional","affiliation":[{"name":"College of Software, Jilin University, Changchun 130012, China"}]},{"given":"Xican","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Software, Jilin University, Changchun 130012, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4075","DOI":"10.3233\/JIFS-200465","article-title":"Next point-of-interest recommendation by sequential feature mining and public preference awareness","volume":"40","author":"Shi","year":"2021","journal-title":"J. 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