{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T16:02:56Z","timestamp":1774713776437,"version":"3.50.1"},"reference-count":29,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Data &amp; Knowledge Engineering"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1016\/j.datak.2025.102414","type":"journal-article","created":{"date-parts":[[2025,2,15]],"date-time":"2025-02-15T21:08:11Z","timestamp":1739653691000},"page":"102414","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":3,"special_numbering":"C","title":["Evaluating diabetes dataset for knowledge graph embedding based link prediction"],"prefix":"10.1016","volume":"157","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3768-5384","authenticated-orcid":false,"given":"Sushmita","family":"Singh","sequence":"first","affiliation":[]},{"given":"Manvi","family":"Siwach","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.datak.2025.102414_b1","article-title":"Lisa Ehrlinger and Wolfram wob: Towards a definition of knowledge graphs","author":"Ehrlinger","year":"2016","journal-title":"Semant.- Web- J."},{"key":"10.1016\/j.datak.2025.102414_b2","doi-asserted-by":"crossref","DOI":"10.13052\/jwe1540-9589.2147","article-title":"Handling heterogeneous data in knowledge graphs: A survey","author":"Singh","year":"2022","journal-title":"J. Web Eng."},{"key":"10.1016\/j.datak.2025.102414_b3","series-title":"Global Healthcare Disasters","article-title":"Role of knowledge graphs in analysing epidemic and healthcare disasters","author":"Singh","year":"2022"},{"key":"10.1016\/j.datak.2025.102414_b4","article-title":"Knowledge graph completion: A review","author":"Chen","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.datak.2025.102414_b5","doi-asserted-by":"crossref","unstructured":"Antoine Bordes, Jason Weston, Ronan Collobert, Yoshua Bengio, et al., Learning structured embeddings of knowledge bases, in: Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011.","DOI":"10.1609\/aaai.v25i1.7917"},{"key":"10.1016\/j.datak.2025.102414_b6","unstructured":"Thomas Mikolov, Kai Chen, Greg Corrado, Jeffry Dean, Efficient Estimation of Word Representations in Vector Space, in: 1st International Conference on Learning Representations, Workshop Track Proceedings, 2013."},{"key":"10.1016\/j.datak.2025.102414_b7","unstructured":"Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio, Joint learningof words and meaning representations for opentext semantic parsing, in: International Conference on Artificial Intelligence and Statistics, 2012, pp. 127\u2013135."},{"key":"10.1016\/j.datak.2025.102414_b8","article-title":"Translating embeddings for modelling multi-relational data","author":"Bordes","year":"2013","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.datak.2025.102414_b9","unstructured":"B Yang, W Yih, X He, J Gao, L Deng, Embedding entities and relations for learning and inference in knowledge bases, in: 3rd International Conference on Learning Representations, Conference Track Proceedings, 2015."},{"key":"10.1016\/j.datak.2025.102414_b10","series-title":"Knowledge base completion: Baselines strike back","author":"Kadlec","year":"2017"},{"key":"10.1016\/j.datak.2025.102414_b11","unstructured":"T. Trouillon, J. Welbl, S. Riedel, E. Gaussier, G. Bouchard, Complex embeddings for simple link prediction, in: Proceedings of the 33nd International Conference on Machine Learning, 2016, pp. 2071\u20132080."},{"key":"10.1016\/j.datak.2025.102414_b12","series-title":"7th International Conference on Learning Representations","article-title":"Rotate: Knowledge graph embedding by relational rotation in complex space","author":"Sun","year":"2019"},{"key":"10.1016\/j.datak.2025.102414_b13","series-title":"International Conference on Learning Representations","article-title":"Modeling relation patterns for knowledge graph embedding with rotate","author":"Sun","year":"2019"},{"key":"10.1016\/j.datak.2025.102414_b14","series-title":"Proceedings of the NAACL HLT 2013 Demonstration Session","first-page":"28","article-title":"UMLS::Similarity: Measuring the relatedness and similarity of biomedical concepts","author":"McInnes","year":"2013"},{"key":"10.1016\/j.datak.2025.102414_b15","series-title":"PaperRobot: Incremental Draft Generation of Scientific Ideas","author":"Wang","year":"2019"},{"key":"10.1016\/j.datak.2025.102414_b16","series-title":"Proceedings of the 18th BioNLP Workshop and Shared Task","article-title":"Embedding biomedical ontologies by jointly encoding network structure and textual node descriptors","author":"Kotitsas","year":"2019"},{"key":"10.1016\/j.datak.2025.102414_b17","unstructured":"Tobias Mayer, Elena Cabrio, Serena Villata, Transformer-based Argument Mining for Healthcare Applications, in: ECAI 24th European Conference on Artificial Intelligence, 2020."},{"key":"10.1016\/j.datak.2025.102414_b18","unstructured":"https:\/\/www.who.int."},{"key":"10.1016\/j.datak.2025.102414_b19","unstructured":"https:\/\/www.cdc.gov."},{"key":"10.1016\/j.datak.2025.102414_b20","unstructured":"https:\/\/www.diabetes.org.uk."},{"key":"10.1016\/j.datak.2025.102414_b21","unstructured":"https:\/\/www.nih.gov."},{"key":"10.1016\/j.datak.2025.102414_b22","doi-asserted-by":"crossref","unstructured":"S Auer, C Bizer, G Kobilarov, J Lehmann, R Cyganiak, Z.G. Ives, DBpedia: A nucleus for a web of open data, in: Proceedings of International Semantic Web Conference, 2007, pp. 722\u2013735.","DOI":"10.1007\/978-3-540-76298-0_52"},{"key":"10.1016\/j.datak.2025.102414_b23","unstructured":"https:\/\/vos.openlinksw.com\/owiki\/wiki\/VOS\/VOSSPARQL."},{"issue":"10","key":"10.1016\/j.datak.2025.102414_b24","doi-asserted-by":"crossref","DOI":"10.14778\/2732951.2732962","article-title":"From data fusion to knowledge fusion","volume":"7","author":"Dong","year":"2014","journal-title":"Proc. VLDB Endow."},{"key":"10.1016\/j.datak.2025.102414_b25","article-title":"Graph embedding techniques","author":"Goyal","year":"2018","journal-title":"Appl. Perform.: Surv. Knowl.- Based Syst."},{"key":"10.1016\/j.datak.2025.102414_b26","doi-asserted-by":"crossref","unstructured":"Yichen Song, Aiping Li, Yan Jia, Jiuming Huang, Xiaojuan Zhao, Knowledge Fusion: Introduction of Concepts and Techniques, in: IEEE Fourth International Conference on Data Science in Cyberspace, DSC, 2019.","DOI":"10.1109\/DSC.2019.00025"},{"key":"10.1016\/j.datak.2025.102414_b27","series-title":"Multi-Source Knowledge Fusion: A Survey","author":"Zhao","year":"2020"},{"key":"10.1016\/j.datak.2025.102414_b28","doi-asserted-by":"crossref","DOI":"10.1155\/2017\/2858423","article-title":"Semantic health knowledge graph: Semantic integration of heterogeneous medical knowledge and services","author":"Shi","year":"2017","journal-title":"BioMed Res. Int."},{"issue":"2","key":"10.1016\/j.datak.2025.102414_b29","doi-asserted-by":"crossref","DOI":"10.1145\/3440755","article-title":"Evolution of semantic similarity\u2014A survey","volume":"54","author":"Chandrasekaran","year":"2021","journal-title":"ACM Comput. Surv."}],"container-title":["Data &amp; Knowledge Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169023X25000096?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169023X25000096?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,3,9]],"date-time":"2025-03-09T01:22:08Z","timestamp":1741483328000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169023X25000096"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":29,"alternative-id":["S0169023X25000096"],"URL":"https:\/\/doi.org\/10.1016\/j.datak.2025.102414","relation":{},"ISSN":["0169-023X"],"issn-type":[{"value":"0169-023X","type":"print"}],"subject":[],"published":{"date-parts":[[2025,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Evaluating diabetes dataset for knowledge graph embedding based link prediction","name":"articletitle","label":"Article Title"},{"value":"Data & Knowledge Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.datak.2025.102414","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"102414"}}