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Constructed by knowledge graphs, the model integrates spatiotemporal features and takes into account the dynamic preferences of users across various temporal, spatial, and situational contexts. Therefore, DRSKG not only describes the spatiotemporal characteristics of user behaviors more accurately but also models the evolution of dynamic preferences in spatiotemporal changes. Massive experiments demonstrate that the proposed model exhibits significant recommendation enhancement compared with the traditional one, achieving up to 7% and 5% improvements in terms of Precision and Recall metrics, respectively.<\/jats:p>","DOI":"10.1007\/s40747-024-01658-y","type":"journal-article","created":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T03:39:18Z","timestamp":1731901158000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A dynamic preference recommendation model based on spatiotemporal knowledge graphs"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-8564-7511","authenticated-orcid":false,"given":"Xinyu","family":"Fan","sequence":"first","affiliation":[]},{"given":"Yinqin","family":"Ji","sequence":"additional","affiliation":[]},{"given":"Bei","family":"Hui","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,18]]},"reference":[{"key":"1658_CR1","doi-asserted-by":"publisher","first-page":"13559","DOI":"10.1007\/s11042-020-10386-7","volume":"80","author":"S Yousefian\u00a0Jazi","year":"2021","unstructured":"Yousefian\u00a0Jazi S, Kaedi M, Fatemi A (2021) An emotion-aware music recommender system: bridging the user\u2019s interaction and music recommendation. 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