Multi-label Hierarchical Text Classification using the ACM Taxonomy

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Fátima
Data de Publicação: 2009
Outros Autores: Santos, António Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/10438
Resumo: Many of the works of text classification involve the attribution of each text a single class label from a predefined set of classes, usually small and flat organized (flat classification). However, there are more complex classification problems in which we can assign to each text more than one class (multi-label classification), that can be organized in a hierarchical structure (hierarchical classification) to support thematic searches by browsing topics of interests. In this paper, a problem of multi-label hierarchical text classification is presented. The experiment involves the creation of a multi-label hierarchical text collection, its pre-processing, followed by the application of different classifiers to the collection, and finally, the evaluation of the classifiers performance.
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spelling Multi-label Hierarchical Text Classification using the ACM TaxonomyMulti-label hierarchical text classificationACM taxonomyMany of the works of text classification involve the attribution of each text a single class label from a predefined set of classes, usually small and flat organized (flat classification). However, there are more complex classification problems in which we can assign to each text more than one class (multi-label classification), that can be organized in a hierarchical structure (hierarchical classification) to support thematic searches by browsing topics of interests. In this paper, a problem of multi-label hierarchical text classification is presented. The experiment involves the creation of a multi-label hierarchical text collection, its pre-processing, followed by the application of different classifiers to the collection, and finally, the evaluation of the classifiers performance.Repositório Científico do Instituto Politécnico do PortoRodrigues, FátimaSantos, António Paulo2017-11-15T11:27:09Z2009-102009-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/10438enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:43:17Zoai:recipp.ipp.pt:10400.22/10438Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:24:27.404649Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Multi-label Hierarchical Text Classification using the ACM Taxonomy
title Multi-label Hierarchical Text Classification using the ACM Taxonomy
spellingShingle Multi-label Hierarchical Text Classification using the ACM Taxonomy
Rodrigues, Fátima
Multi-label hierarchical text classification
ACM taxonomy
title_short Multi-label Hierarchical Text Classification using the ACM Taxonomy
title_full Multi-label Hierarchical Text Classification using the ACM Taxonomy
title_fullStr Multi-label Hierarchical Text Classification using the ACM Taxonomy
title_full_unstemmed Multi-label Hierarchical Text Classification using the ACM Taxonomy
title_sort Multi-label Hierarchical Text Classification using the ACM Taxonomy
author Rodrigues, Fátima
author_facet Rodrigues, Fátima
Santos, António Paulo
author_role author
author2 Santos, António Paulo
author2_role author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Rodrigues, Fátima
Santos, António Paulo
dc.subject.por.fl_str_mv Multi-label hierarchical text classification
ACM taxonomy
topic Multi-label hierarchical text classification
ACM taxonomy
description Many of the works of text classification involve the attribution of each text a single class label from a predefined set of classes, usually small and flat organized (flat classification). However, there are more complex classification problems in which we can assign to each text more than one class (multi-label classification), that can be organized in a hierarchical structure (hierarchical classification) to support thematic searches by browsing topics of interests. In this paper, a problem of multi-label hierarchical text classification is presented. The experiment involves the creation of a multi-label hierarchical text collection, its pre-processing, followed by the application of different classifiers to the collection, and finally, the evaluation of the classifiers performance.
publishDate 2009
dc.date.none.fl_str_mv 2009-10
2009-10-01T00:00:00Z
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