J Biomed Inform - Semantic concept-enriched dependence model for medical information retrieval.

Tópicos

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Resumo

JECTIVE: In medical information retrieval research, semantic resources have been mostly used by expanding the original query terms or estimating the concept importance weight. However, implicit term-dependency information contained in semantic concept terms has been overlooked or at least underused in most previous studies. In this study, we incorporate a semantic concept-based term-dependence feature into a formal retrieval model to improve its ranking performance.DESIGN: Standardized medical concept terms used by medical professionals were assumed to have implicit dependency within the same concept. We hypothesized that, by elaborately revising the ranking algorithms to favor documents that preserve those implicit dependencies, the ranking performance could be improved. The implicit dependence features are harvested from the original query using MetaMap. These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM). We designed four different variants of the model, with each variant having distinct characteristics in the feature formulation method.MEASUREMENTS: We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections in medical information retrieval research.RESULTS: Our semantic concept-enriched dependence model consistently outperformed other state-of-the-art retrieval methods. Analysis shows that the performance gain has occurred independently of the concept's explicit importance in the query.CONCLUSION: By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent of the concept importance.

Resumo Limpo

jectiv medic inform retriev research semant resourc most use expand origin queri term estim concept import weight howev implicit termdepend inform contain semant concept term overlook least underus previous studi studi incorpor semant conceptbas termdepend featur formal retriev model improv rank performancedesign standard medic concept term use medic profession assum implicit depend within concept hypothes elabor revis rank algorithm favor document preserv implicit depend rank perform improv implicit depend featur harvest origin queri use metamap semant conceptbas depend featur incorpor semant conceptenrich depend model scdm design four differ variant model variant distinct characterist featur formul methodmeasur perform leaveoneout cross valid clinic document corpus trec medic record track medic literatur corpus ohsum repres test collect medic inform retriev researchresult semant conceptenrich depend model consist outperform stateoftheart retriev method analysi show perform gain occur independ concept explicit import queryconclus captur implicit knowledg regard queri term relationship incorpor rank model build robust effect retriev model independ concept import

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