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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
03/02/2011 |
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Data da última atualização: |
14/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
MOURA, M. F.; REZENDE, S. O. |
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Afiliação: |
MARIA FERNANDA MOURA, CNPTIA; SOLANGE OLIVEIRA REZENDE, ICMC/USP. |
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Título: |
A simple method for labeling hierarchical document clusters. |
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Ano de publicação: |
2010 |
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Fonte/Imprenta: |
In: IASTED INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND APPLICATIONS, 10., 2010, Innsbruck. Proceedings... Anaheim: ACTA Press. |
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Páginas: |
p. 363-371. |
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ISBN: |
978-0-88986-817-5 |
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Idioma: |
Inglês |
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Notas: |
AIA 2010. |
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Conteúdo: |
One of the problems of automatic models in generating topic taxonomies is the process of creating the most significant word list that discriminates each document group. A proposal for doing this through labeling hierarchical document clusters is presented in this paper. The goal of this method is to aid the construction of topic taxonomies. It aims to be language independent and to produce discriminative labels for each group, without replications of the terms along the hierarchy branches. Moreover the method is cluster independent, that is, it can be applied to any hierarchical cluster result or any hierarchy, even those that are manually produced. In order to reach the goals the method is based on a formal definition of a topic taxonomy, also presented in the paper. The method was implemented and evaluated against three other literature methods through their recalling results in a particular information retrieval process. The proposed method outperformed the other three methods; additionally it has a linear complexity. |
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Palavras-Chave: |
Agrupamento hierárquico; Attribute selection; Cluster labeling; Document clustering; Hierarchical clustering; Mineração de textos; Recuperação da informação; Seleção de atributos; Text mining; Topic taxonomy. |
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Thesagro: |
Taxonomia. |
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Thesaurus Nal: |
Cluster analysis; Information retrieval. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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001 1875648
005 2020-01-14
008 2010 bl uuuu u00u1 u #d
020 $a978-0-88986-817-5
100 1 $aMOURA, M. F.
245 $aA simple method for labeling hierarchical document clusters.$h[electronic resource]
260 $aIn: IASTED INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND APPLICATIONS, 10., 2010, Innsbruck. Proceedings... Anaheim: ACTA Press.$c2010
300 $ap. 363-371.
500 $aAIA 2010.
520 $aOne of the problems of automatic models in generating topic taxonomies is the process of creating the most significant word list that discriminates each document group. A proposal for doing this through labeling hierarchical document clusters is presented in this paper. The goal of this method is to aid the construction of topic taxonomies. It aims to be language independent and to produce discriminative labels for each group, without replications of the terms along the hierarchy branches. Moreover the method is cluster independent, that is, it can be applied to any hierarchical cluster result or any hierarchy, even those that are manually produced. In order to reach the goals the method is based on a formal definition of a topic taxonomy, also presented in the paper. The method was implemented and evaluated against three other literature methods through their recalling results in a particular information retrieval process. The proposed method outperformed the other three methods; additionally it has a linear complexity.
650 $aCluster analysis
650 $aInformation retrieval
650 $aTaxonomia
653 $aAgrupamento hierárquico
653 $aAttribute selection
653 $aCluster labeling
653 $aDocument clustering
653 $aHierarchical clustering
653 $aMineração de textos
653 $aRecuperação da informação
653 $aSeleção de atributos
653 $aText mining
653 $aTopic taxonomy
700 1 $aREZENDE, S. O.
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