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dc.date.accessioned 2010-03-22T11:53:15Z
dc.date.available 2010-03-22T03:00:00Z
dc.date.issued 2010-04
dc.identifier.uri http://hdl.handle.net/10915/9660
dc.description.abstract Research work on "short-text clustering" is a very important research area due to the current tendency for people to use "small-language", e.g. blogs, textmessaging and others. In some recent works, new bioinspired clustering algorithms have been proposed to deal with this difficult problem and novel uses of Internal Clustering Validity Measures have also been presented. In this work, a new AntTree-based approach is proposed for this task. It integrates information on the Silhouette Coefficient and the concept of attraction of a cluster in different stages of the clustering process. The proposal achieves results comparable to the best reported results in this area, showing an interesting stability in the quality of the results and presenting some interesting capabilities as a general improvement method for arbitrary clustering approaches. en
dc.format.extent p. 1-7 es
dc.language en es
dc.title A new AntTree-based algorithm for clustering short-text corpora en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr10-1.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Errecalde, Marcelo Luis es
sedici.creator.person Ingaramo, Diego Alejandro es
sedici.creator.person Rosso, Paolo es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.other short-text clustering en
sedici.subject.other bio-inspired algorithms en
sedici.subject.other internal validity measures en
sedici.subject.other silhouette coefficient en
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000005730 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 10, no. 1 es

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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)