{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T11:08:56Z","timestamp":1764932936568,"version":"3.46.0"},"reference-count":38,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"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":["61402087"],"award-info":[{"award-number":["61402087"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"publisher","award":["F2022501015"],"award-info":[{"award-number":["F2022501015"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Project Fund of the Center of National Railway Intelligent Transportation System Engineering and Technology","award":["RITS2023KF04"],"award-info":[{"award-number":["RITS2023KF04"]}]},{"name":"Key Project Fund of China Academy of Railway Sciences Corporation Limited","award":["2023YJ363"],"award-info":[{"award-number":["2023YJ363"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Approximate query on knowledge graphs (KGs) is an important and common task in real-world applications, where the goal is to return more results on KGs that match the query criteria. Previous approximate query methods have focused on static KGs. However, many KGs in real-world applications are dynamic and evolve over time. In this paper, we consider approximate queries in temporal knowledge graphs (TKGs) that may have specific timestamps in the predicates. We propose a Two-Level Approximate Query method (TLAQ) for temporal knowledge graphs based on the two-level embedding of vertex and graph. Specifically, we first improve the eigenmatrix of the GCN to enhance the embedding representation. On this basis, TLAQ defines relational reliability and attributive confidence at the vertex level. Then, we unify the encoding format of timestamps at the graph level to further strengthen the embedding model. Finally, we demonstrate the effectiveness of our proposed approach through a comprehensive experiment.<\/jats:p>","DOI":"10.3390\/e27121232","type":"journal-article","created":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T10:50:38Z","timestamp":1764931838000},"page":"1232","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Approximate Query on Temporal Knowledge Graphs via Two-Level Embeddings"],"prefix":"10.3390","volume":"27","author":[{"given":"Jiaxuan","family":"Liu","sequence":"first","affiliation":[{"name":"Sydney Smart Technology College, Northeastern University, Qinhuangdao 066004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyi","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9546-3208","authenticated-orcid":false,"given":"Luyi","family":"Bai","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, Northeastern University (Qinhuangdao), Qinhuangdao 066004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.websem.2009.07.002","article-title":"DBpedia\u2014A crystallization point for the web of data","volume":"7","author":"Bizer","year":"2009","journal-title":"J. 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