J Biomed Inform - A framework for unifying ontology-based semantic similarity measures: a study in the biomedical domain.

Tópicos

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Resumo

Ontologies are widely adopted in the biomedical domain to characterize various resources (e.g. diseases, drugs, scientific publications) with non-ambiguous meanings. By exploiting the structured knowledge that ontologies provide, a plethora of ad hoc and domain-specific semantic similarity measures have been defined over the last years. Nevertheless, some critical questions remain: which measure should be defined/chosen for a concrete application? Are some of the, a priori different, measures indeed equivalent? In order to bring some light to these questions, we perform an in-depth analysis of existing ontology-based measures to identify the core elements of semantic similarity assessment. As a result, this paper presents a unifying framework that aims to improve the understanding of semantic measures, to highlight their equivalences and to propose bridges between their theoretical bases. By demonstrating that groups of measures are just particular instantiations of parameterized functions, we unify a large number of state-of-the-art semantic similarity measures through common expressions. The application of the proposed framework and its practical usefulness is underlined by an empirical analysis of hundreds of semantic measures in a biomedical context.

Resumo Limpo

ontolog wide adopt biomed domain character various resourc eg diseas drug scientif public nonambigu mean exploit structur knowledg ontolog provid plethora ad hoc domainspecif semant similar measur defin last year nevertheless critic question remain measur definedchosen concret applic priori differ measur inde equival order bring light question perform indepth analysi exist ontologybas measur identifi core element semant similar assess result paper present unifi framework aim improv understand semant measur highlight equival propos bridg theoret base demonstr group measur just particular instanti parameter function unifi larg number stateoftheart semant similar measur common express applic propos framework practic use underlin empir analysi hundr semant measur biomed context

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