Semantic matching for the medical domain

Shamdasani, Jetendr; Bloodsworth, Peter; McClatchey, Richard

Abstract

This paper proposes some modifications to the SMatch algorithm that enables the semantic matching of medical terminologies using the Unified Medical Language System (UMLS) as a source of background knowledge. Semantic Matching is the process of discovering set theoretic relationships between differing data elements. Initial results from the domain of anatomy are presented that illustrate how semantic relationships can provide greater information during the ontology alignment process than equivalence relationships alone. The paper concludes by demonstrating how this is beneficial in the medical domain. © 2008 Springer-Verlag Berlin Heidelberg.

Citation

Shamdasani, J., Bloodsworth, P., & McClatchey, R. (2008). Semantic matching for the medical domain. Lecture Notes in Artificial Intelligence, 5071 LNCS, 198-202. https://doi.org/10.1007/978-3-540-70504-8_21

• Journal Article Type: Conference Paper
• Publication Date: Oct 27, 2008
• Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
• Print ISSN: 0302-9743
• Electronic ISSN: 1611-3349
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 5071 LNCS
• Pages: 198-202
• DOI: https://doi.org/10.1007/978-3-540-70504-8_21
• Keywords: database systems, knowledge based systems, ontology, semantics, background knowledges, data elements, equivalence relationships, GREAT-ER, medical domains, medical terminologies, ontology alignments, semantic matching, semantic relationships, unified medi
• Public URL: https://uwe-repository.worktribe.com/output/1021841
• Publisher URL: http://dx.doi.org/10.1007/978-3-540-70504-8_21