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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
31/07/2012 |
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Data da última atualização: |
08/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
LEITE, M. A. A.; RICARTE, I. L. M. |
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Afiliação: |
MARIA ANGELICA ANDRADE LEITE, CNPTIA; IVAN LUIZ MARQUES RICARTE, FEEC/Unicamp. |
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Título: |
Relating ontologies with a fuzzy information model. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Knowledge and Information Systems, London, 2012. |
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Páginas: |
Não paginado. |
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DOI: |
10.1007/s10115-012-0482-0 |
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Idioma: |
Inglês |
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Conteúdo: |
More people than ever before have access to information with the World Wide Web; information volume and number of users both continue to expand. Traditional search methods based on keywords are not effective, resulting in large lists of documents, many of which unrelated to users? needs. One way to improve information retrieval is to associate meaning to users? queries by using ontologies, knowledge bases that encode a set of concepts about one domain and their relationships. Encoding a knowledge base using one single ontology is usual, but a document collection can deal with different domains, each organized into an ontology. This work presents a novel way to represent and organize knowledge, from distinct domains, using multiple ontologies that can be related. The model allows the ontologies, as well as the relationships between concepts from distinct ontologies, to be represented independently. Additionally, fuzzy set theory techniques are employed to deal with knowledge subjectivity and uncertainty. This approach to organize knowledge and an associated query expansion method are integrated into a fuzzy model for information retrieval based on multi-related ontologies. The performance of a search engine using this model is compared with another fuzzy-based approach for information retrieval, and with the Apache Lucene search engine. Experimental results show that this model improves precision and recall measures. |
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Palavras-Chave: |
Modelo fuzzy; Ontologias; Organização da informação. |
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Thesaurus Nal: |
Fuzzy logic. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02029naa a2200205 a 4500
001 1929972
005 2020-01-08
008 2012 bl uuuu u00u1 u #d
024 7 $a10.1007/s10115-012-0482-0$2DOI
100 1 $aLEITE, M. A. A.
245 $aRelating ontologies with a fuzzy information model.$h[electronic resource]
260 $c2012
300 $aNão paginado.
520 $aMore people than ever before have access to information with the World Wide Web; information volume and number of users both continue to expand. Traditional search methods based on keywords are not effective, resulting in large lists of documents, many of which unrelated to users? needs. One way to improve information retrieval is to associate meaning to users? queries by using ontologies, knowledge bases that encode a set of concepts about one domain and their relationships. Encoding a knowledge base using one single ontology is usual, but a document collection can deal with different domains, each organized into an ontology. This work presents a novel way to represent and organize knowledge, from distinct domains, using multiple ontologies that can be related. The model allows the ontologies, as well as the relationships between concepts from distinct ontologies, to be represented independently. Additionally, fuzzy set theory techniques are employed to deal with knowledge subjectivity and uncertainty. This approach to organize knowledge and an associated query expansion method are integrated into a fuzzy model for information retrieval based on multi-related ontologies. The performance of a search engine using this model is compared with another fuzzy-based approach for information retrieval, and with the Apache Lucene search engine. Experimental results show that this model improves precision and recall measures.
650 $aFuzzy logic
653 $aModelo fuzzy
653 $aOntologias
653 $aOrganização da informação
700 1 $aRICARTE, I. L. M.
773 $tKnowledge and Information Systems, London, 2012.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Origem |
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Registro |
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URL |
Voltar
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Registro Completo
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
12/05/2006 |
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Data da última atualização: |
15/10/2014 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
Internacional - A |
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Autoria: |
LU, D.; MAUSEL, P.; BATISTELLA, M.; MORAN, E. |
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Afiliação: |
Indiana University-CIPEC (1, 3-4); Embrapa Monitoramento por Satélite (2). |
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Título: |
Land-cover binary change detection methods for use in the moist tropical region of the Amazon: a comparative study. |
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Ano de publicação: |
2005 |
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Fonte/Imprenta: |
International Journal of Remote Sensing, v. 26, n. 1, jan. 2005, p. 101-114. |
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Páginas: |
14 p. |
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Descrição Física: |
folhas avulsas |
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DOI: |
10. 10S0I0143 li 60410001720748 |
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Idioma: |
Inglês |
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Conteúdo: |
Many land-cover change detection techniques have been developed; however, different conclusions about the value or appropriateness of each exist. This difference of opinion is often influenced by the landscape complexity of study areas and data used for analysis. Which method is most suitable for land-cover change detection in Amazon tropical regions remains unclear. ln this paper, 10 binary change detection methods were implemented and compared with respect to their capability to detect land-cover change and no change conditions in moist tropical regions. They are image differencing (ID), modified image differencing (MID), a combination of image differencing and principal component analysis (IDPCA), principal component differencing (PCD), multitemporal PCA (MPCA), change vector analysis (CVA), vegetation index differencing (VID), image ratioing (IR), modified image ratioing (MIR), and a combination of image ratioing and PCA (lRPCA). Multi-temporal Thematic Mapper (TM) data were used to conduct land-cover binary change detection. Research results indicate that MID, PCD and ID using TM band 5 are significant1y better than other binary change detection methods and they are recommended specifically for implementation in the Amazon basin. |
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Palavras-Chave: |
Amazonas; Monitoramento; Região Amazônica. |
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Thesagro: |
Satélite; Vegetação. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/109991/1/1800.pdf
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Marc: |
LEADER 01981naa a2200241 a 4500
001 1017488
005 2014-10-15
008 2005 bl uuuu u00u1 u #d
024 7 $a10. 10S0I0143 li 60410001720748$2DOI
100 1 $aLU, D.
245 $aLand-cover binary change detection methods for use in the moist tropical region of the Amazon$ba comparative study.
260 $c2005
300 $a14 p.$cfolhas avulsas
520 $aMany land-cover change detection techniques have been developed; however, different conclusions about the value or appropriateness of each exist. This difference of opinion is often influenced by the landscape complexity of study areas and data used for analysis. Which method is most suitable for land-cover change detection in Amazon tropical regions remains unclear. ln this paper, 10 binary change detection methods were implemented and compared with respect to their capability to detect land-cover change and no change conditions in moist tropical regions. They are image differencing (ID), modified image differencing (MID), a combination of image differencing and principal component analysis (IDPCA), principal component differencing (PCD), multitemporal PCA (MPCA), change vector analysis (CVA), vegetation index differencing (VID), image ratioing (IR), modified image ratioing (MIR), and a combination of image ratioing and PCA (lRPCA). Multi-temporal Thematic Mapper (TM) data were used to conduct land-cover binary change detection. Research results indicate that MID, PCD and ID using TM band 5 are significant1y better than other binary change detection methods and they are recommended specifically for implementation in the Amazon basin.
650 $aSatélite
650 $aVegetação
653 $aAmazonas
653 $aMonitoramento
653 $aRegião Amazônica
700 1 $aMAUSEL, P.
700 1 $aBATISTELLA, M.
700 1 $aMORAN, E.
773 $tInternational Journal of Remote Sensing$gv. 26, n. 1, jan. 2005, p. 101-114.
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