Work

Comparing Associative Relationships among Equivalent Concepts across Ontologies

Year: 2004

Type: book-chapter

Abstract: Methods for comparing associative relationships across ontologies often rely solely on lexical similarity between the names of the relationships, which may lead to missed matches and inaccurate matches. In this paper, we propose a novel method based on the analysis of paths between equivalent concepts across ontologies. Patterns of relationships are identified for each associative relationship. The most frequent patterns indicate a correspondence between an associative relationship in one ontology and one relationship (or combination thereof) in the other. We applied this method to two ontologies of anatomy. Our method was able to identify the correspondence between relationships even in the absence of lexical similarity between relationship names. The various types of matches identified are discussed as well as the application of this method to detecting inconsistencies across the ontologies.

Source: Studies in health technology and informatics

DOI: 10.3233/978-1-60750-949-3-459

Authors: Zhang Songmao, Bodenreider Olivier

Institution: United States National Library of Medicine

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funder: National Institutes of Health

Award: G202981822