{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T05:46:53Z","timestamp":1762062413075,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T00:00:00Z","timestamp":1738972800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Jiangsu Province","award":["BK20241070","YK23-05-01","F2023207003","24KJD510005"],"award-info":[{"award-number":["BK20241070","YK23-05-01","F2023207003","24KJD510005"]}]},{"name":"Start-up Fund for New Talented Researchers of Nanjing Vocational University of Industry Technology","award":["BK20241070","YK23-05-01","F2023207003","24KJD510005"],"award-info":[{"award-number":["BK20241070","YK23-05-01","F2023207003","24KJD510005"]}]},{"DOI":"10.13039\/501100003787","name":"Hebei Natural Science Foundation","doi-asserted-by":"publisher","award":["BK20241070","YK23-05-01","F2023207003","24KJD510005"],"award-info":[{"award-number":["BK20241070","YK23-05-01","F2023207003","24KJD510005"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Research of Jiangsu Higher Education Institutions of China","award":["BK20241070","YK23-05-01","F2023207003","24KJD510005"],"award-info":[{"award-number":["BK20241070","YK23-05-01","F2023207003","24KJD510005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Point-of-interest (POI) recommendation is highly sensitive to temporal factors, including fluctuations in user preferences, variation in user similarity, and decay in the attraction of locations. However, current studies overlook the temporal dynamics of user similarity and the timeliness of POIs, resulting in a disconnect between recommendations and users\u2019 recent preferences. This paper proposes a new framework for dynamic and timely POI recommendation by integrating spatio-temporal influences and social relationships. Dynamic prediction is achieved through an enhanced user-based collaborative filtering approach. A time slot clustering technique was designed based on the statistical check-in features in each time slot. Ratings within the same cluster were shared to address data sparsity. To reflect user similarity drift, we took the time variable as a crucial parameter to dynamically calculate user similarity. Moreover, timely prediction was achieved by integrating the timeliness, popularity, and spatial features of POIs. We introduce a novel method to evaluate the timeliness of POI recommendation, aimed at assessing whether the recommendations align with users\u2019 recent preferences. Comprehensive experiments are performed on Brightkite and Gowalla datasets, with the data divided into workdays and weekends. The experimental results reveal that our algorithm outperforms seven state-of-the-art recommenders in terms of prediction accuracy and system timeliness.<\/jats:p>","DOI":"10.3390\/ijgi14020068","type":"journal-article","created":{"date-parts":[[2025,2,12]],"date-time":"2025-02-12T08:05:42Z","timestamp":1739347542000},"page":"68","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Dynamic and Timely Point-of-Interest Recommendation Based on Spatio-Temporal Influences, Timeliness Feature and Social Relationships"],"prefix":"10.3390","volume":"14","author":[{"given":"Jun","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Computer and Software, Nanjing Vocational University of Industry Technology, Nanjing 210023, China"},{"name":"College of Computer Science and Software Engineering, Hohai University, Nanjing 211100, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3835-6075","authenticated-orcid":false,"given":"Haifeng","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology & Artificial Intelligence, Nanjing Forestry University, Nanjing 210037, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4421-273X","authenticated-orcid":false,"given":"Zhinan","family":"Gou","sequence":"additional","affiliation":[{"name":"School of Management Science and Information Engineering, Hebei University of Economics and Business, Shijiazhuang 050061, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7962-6668","authenticated-orcid":false,"given":"Yiqing","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer and Software, Nanjing Vocational University of Industry Technology, Nanjing 210023, China"}]},{"given":"Hongying","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Nanjing University of Science and Technology Zijin College, Nanjing 210023, China"}]},{"given":"Ming","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Computer and Software, Nanjing Vocational University of Industry Technology, Nanjing 210023, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2054-1392","authenticated-orcid":false,"given":"Li","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Software, Nanjing Vocational University of Industry Technology, Nanjing 210023, China"}]},{"given":"Shu","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Hohai University, Nanjing 211100, China"}]},{"given":"Bing","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Hohai University, Nanjing 211100, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Darapisut, S., Amphawan, K., Leelathakul, N., and Rimcharoen, S. 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