{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T00:59:51Z","timestamp":1768611591312,"version":"3.49.0"},"reference-count":40,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["41871364"],"award-info":[{"award-number":["41871364"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["41571397"],"award-info":[{"award-number":["41571397"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["41871276"],"award-info":[{"award-number":["41871276"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["51678077"],"award-info":[{"award-number":["51678077"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Multi-source spatio-temporal data analysis is an important task in the development of smart cities. However, traditional data analysis methods cannot adapt to the growth rate of massive multi-source spatio-temporal data and explain the practical significance of results. To explore the network structure and semantic relationships, we propose a general framework for multi-source spatio-temporal data analysis via knowledge graph embedding. The framework extracts low-dimensional feature representation from multi-source spatio-temporal data in a high-dimensional space, and recognizes the network structure and semantic relationships about multi-source spatio-temporal data. Experiment results show that the framework can not only effectively utilize multi-source spatio-temporal data, but also explore the network structure and semantic relationship. Taking real Shanghai datasets as an example, we confirm the validity of the multi-source spatio-temporal data analytical framework based on knowledge graph embedding.<\/jats:p>","DOI":"10.3390\/sym12020199","type":"journal-article","created":{"date-parts":[[2020,2,3]],"date-time":"2020-02-03T01:25:51Z","timestamp":1580693151000},"page":"199","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Urban Multi-Source Spatio-Temporal Data Analysis Aware Knowledge Graph Embedding"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6103-1113","authenticated-orcid":false,"given":"Ling","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410012, China"}]},{"given":"Hanhan","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410012, China"}]},{"given":"Linyao","family":"Qiu","sequence":"additional","affiliation":[{"name":"China Academy of Electronic and Information Technology, Beijing 100086, China"}]},{"given":"Sumin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Architecture, Changsha University of Science and Technology, Changsha 610059, China"}]},{"given":"Zhixiang","family":"Hou","sequence":"additional","affiliation":[{"name":"School of Architecture, Changsha University of Science and Technology, Changsha 610059, China"}]},{"given":"Hai","family":"Sun","sequence":"additional","affiliation":[{"name":"China Telecom Shanghai Ideal Information Industry (Group) Co., Ltd., Shanghai 200120, China"}]},{"given":"Yun","family":"Chen","sequence":"additional","affiliation":[{"name":"Shanghai Aerospace Control Technology Institute, Shanghai 201109, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,1]]},"reference":[{"key":"ref_1","unstructured":"Uselton, S.P., Treinish, L., and Ahrens, J.P. 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