Author, as appears in the article.: Sanchez, David; Sole-Ribalta, Albert; Batet, Montserrat; Serratosa, Francesc
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: Batet Sanromà, Montserrat / Sánchez Ruenes, David / Serratosa Casanelles, Francesc d'Assís / Solé Ribalta, Albert
Keywords: Wordnet Word net Web Unified medical language system Semantics Semantic similarity Semantic knowledge Multiple ontologies Mesh Medical subject headings Medical informatics Graph edit distance Computation Algorithms
Abstract: The estimation of the semantic similarity between terms provides a valuable tool to enable the understanding of textual resources. Many semantic similarity computation paradigms have been proposed both as general-purpose solutions or framed in concrete fields such as biomedicine. In particular, ontology-based approaches have been very successful due to their efficiency, scalability, lack of constraints and thanks to the availability of large and consensus ontologies (like Word Net or those in the UMLS). These measures, however, are hampered by the fact that only one ontology is exploited and, hence, their recall depends on the ontological detail and coverage. In recent years, some authors have extended some of the existing methodologies to support multiple ontologies. The problem of integrating heterogeneous knowledge sources is tackled by means of simple terminological matchings between ontological concepts. In this paper, we aim to improve these methods by analysing the similarity between the modelled taxonomical knowledge and the structure of different ontologies. As a result, we are able to better discover the commonalities between different ontologies and hence, improve the accuracy of the similarity estimation. Two methods are proposed to tackle this task. They have been evaluated and compared with related works by means of several widely-used benchmarks of biomedical terms using two standard ontologies (Word Net and MeSH). Results show that our methods correlate better, compared to related works, with the similarity assessments provided by experts in biomedicine. (C) 2011 Elsevier Inc. All rights reserved.
Thematic Areas: Saúde coletiva Medical informatics Mathematical & computational biology Interdisciplinar Health informatics Ensino Engenharias iv Computer science, interdisciplinary applications Computer science applications Ciências biológicas i Ciência da computação
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: montserrat.batet@urv.cat albert.sole@urv.cat david.sanchez@urv.cat francesc.serratosa@urv.cat
Author identifier: 0000-0001-8174-7592 0000-0002-2953-5338 0000-0001-7275-7887 0000-0001-6112-5913
Record's date: 2024-10-12
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.sciencedirect.com/science/article/pii/S1532046411001717?via%3Dihub
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Journal Of Biomedical Informatics. 45 (1): 141-155
APA: Sanchez, David; Sole-Ribalta, Albert; Batet, Montserrat; Serratosa, Francesc (2012). Enabling semantic similarity estimation across multiple ontologies: An evaluation in the biomedical domain. Journal Of Biomedical Informatics, 45(1), 141-155. DOI: 10.1016/j.jbi.2011.10.005
Article's DOI: 10.1016/j.jbi.2011.10.005
Entity: Universitat Rovira i Virgili
Journal publication year: 2012
Publication Type: Journal Publications