Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/10213

TítuloBioDR : semantic indexing networks for biomedical document retrieval
Autor(es)Lourenço, Anália
Carreira, Rafael
Glez-Peña, Daniel
Méndez, José R.
Carneiro, S.
Rocha, Luís M.
Díaz, Fernando
Ferreira, E. C.
Rocha, I.
Fdez-Riverola, Florentino
Rocha, Miguel
Palavras-chaveBiomedical document retrieval
Document relevance
Enhanced Instance Retrieval Network
Named entity recognition
Semantic indexing document network
EditoraElsevier Ltd.
RevistaExpert Systems with Applications
Citação"Expert Systems with Applications". ISSN 0957-4174. 37:4 (Apr. 2010) 3444-3453.
Resumo(s)In Biomedical research, retrieving documents that match an interesting query is a task performed quite frequently. Typically, the set of obtained results is extensive containing many non-interesting documents and consists in a flat list, i.e., not organized or indexed in any way. This work proposes BioDR, a novel approach that allows the semantic indexing of the results of a query, by identifying relevant terms in the documents. These terms emerge from a process of Named Entity Recognition that annotates occurrences of biological terms (e.g. genes or proteins) in abstracts or full-texts. The system is based on a learning process that builds an Enhanced Instance Retrieval Network (EIRN) from a set of manually classified documents, regarding their relevance to a given problem. The resulting EIRN implements the semantic indexing of documents and terms, allowing for enhanced navigation and visualization tools, as well as the assessment of relevance for new documents.
Arbitragem científicayes
Aparece nas coleções:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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