Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/01/2010 |
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Data da última atualização: |
15/01/2020 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
LEITE, M. A. de A.; RICARTE, I. L. M. |
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Afiliação: |
MARIA ANGELICA DE ANDRADE LEITE, CNPTIA; IVAN L. M. RICARTE, FEEC/UNICAMP. |
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Título: |
Fuzzy Information Retrieval Model Based on Multiple Related Ontologies. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: ENCONTRO DOS ALUNOS E DOCENTES DO DEPARTAMENTO DE ENGENHARIA DE COMPUTAÇÃO E AUTOMAÇÃO INDUSTRIAL, 2., 2009, Campinas. Anais... Campinas: UNICAMP, 2009. |
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Páginas: |
p. 93-96. |
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Idioma: |
Inglês |
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Notas: |
EADCA 2009. |
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Conteúdo: |
With the World Wide Web popularity the information retrieval area has a new challenge intending to retrieve information resources by their meaning by using a knowledge base. Nowadays ontologies are being used to model knowledge bases. To deal with knowledge subjectivity and uncertainty fuzzy set theory techniques are employed. Preceding works encode a knowledge base using just one ontology. But a document collection can deal with different domain themes, expressed by distinct ontologies. In this work a way of knowledge organization and representation as multiple related ontologies was investigated and a method of query expansion was developed. The knowledge organization and the query expansion method were integrated in the fuzzy model for information retrieval based on mutiple related ontologies. The model performance was compared with another fuzzy-based approach for information retrieval and with the Apache Lucene search engine. In both cases the proposed model improves the precision and recall measures. |
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Palavras-Chave: |
Fuzzy; Fuzzy Information Retrieval; Knowledge Representation; Ontologias; Ontology; Query Expansion; Recuperação de informação. |
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Thesaurus NAL: |
Fuzzy logic; Information retrieval. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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100 1 $aLEITE, M. A. de A.
245 $aFuzzy Information Retrieval Model Based on Multiple Related Ontologies.$h[electronic resource]
260 $aIn: ENCONTRO DOS ALUNOS E DOCENTES DO DEPARTAMENTO DE ENGENHARIA DE COMPUTAÇÃO E AUTOMAÇÃO INDUSTRIAL, 2., 2009, Campinas. Anais... Campinas: UNICAMP$c2009
300 $ap. 93-96.
500 $aEADCA 2009.
520 $aWith the World Wide Web popularity the information retrieval area has a new challenge intending to retrieve information resources by their meaning by using a knowledge base. Nowadays ontologies are being used to model knowledge bases. To deal with knowledge subjectivity and uncertainty fuzzy set theory techniques are employed. Preceding works encode a knowledge base using just one ontology. But a document collection can deal with different domain themes, expressed by distinct ontologies. In this work a way of knowledge organization and representation as multiple related ontologies was investigated and a method of query expansion was developed. The knowledge organization and the query expansion method were integrated in the fuzzy model for information retrieval based on mutiple related ontologies. The model performance was compared with another fuzzy-based approach for information retrieval and with the Apache Lucene search engine. In both cases the proposed model improves the precision and recall measures.
650 $aFuzzy logic
650 $aInformation retrieval
653 $aFuzzy
653 $aFuzzy Information Retrieval
653 $aKnowledge Representation
653 $aOntologias
653 $aOntology
653 $aQuery Expansion
653 $aRecuperação de informação
700 1 $aRICARTE, I. L. M.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
