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dc.contributor.author
Errecalde, Marcelo L.  
dc.contributor.author
Cagnina, Leticia Cecilia  
dc.contributor.author
Rosso, Paolo  
dc.date.available
2016-08-12T17:02:51Z  
dc.date.issued
2015-08-14  
dc.identifier.citation
Errecalde, Marcelo L.; Cagnina, Leticia Cecilia; Rosso, Paolo; Silhouette + Attraction: A Simple and Effective Method for Text Clustering; Cambridge University Press; Natural Language Engineering; 1; 14-8-2015; 1-40  
dc.identifier.issn
1351-3249  
dc.identifier.uri
http://hdl.handle.net/11336/7135  
dc.description.abstract
This article presents Sil-Att, a simple and effective method for text clustering, which is based on two main concepts: the silhouette coefficient and the idea of attraction. The combination of both principles allows to obtain a general technique that can be used either as a boosting method, which improves results of other clustering algorithms, or as an independent clustering algorithm. The experimental work shows that Sil-Att is able to obtain high quality results on text corpora with very different characteristics. Furthermore, its stable performance on all the considered corpora is indicative that it is a very robust method. This is a very interesting positive aspect of Sil-Att with respect to the other algorithms used in the experiments, whose performances heavily depend on specific characteristics of the corpora being considered.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Cambridge University Press  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Clustering  
dc.subject
Short Texts Corpora  
dc.subject
Attraction  
dc.subject
Silhouette  
dc.subject.classification
Otras Ciencias de la Computación e Información  
dc.subject.classification
Ciencias de la Computación e Información  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Silhouette + Attraction: A Simple and Effective Method for Text Clustering  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2016-08-04T17:24:49Z  
dc.journal.volume
1  
dc.journal.pagination
1-40  
dc.journal.pais
Reino Unido  
dc.journal.ciudad
Cambridge  
dc.description.fil
Fil: Errecalde, Marcelo L.. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Informática. Laboratorio Investigación y Desarrollo En Inteligencia Computacional; Argentina  
dc.description.fil
Fil: Cagnina, Leticia Cecilia. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Informática. Laboratorio Investigación y Desarrollo En Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Rosso, Paolo. Universidad Politecnica de Valencia; España  
dc.journal.title
Natural Language Engineering  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1017/S1351324915000273  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=9910907