dc.creatorErrecalde, Marcelo Luis
dc.creatorIngaramo, Diego Alejandro
dc.creatorRosso, Paolo
dc.date2010-04
dc.date2010-03-22T03:00:00Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/9660
dc.identifierhttp://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr10-1.pdf
dc.identifierissn:1666-6038
dc.descriptionResearch 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.
dc.descriptionFacultad de Informática
dc.formatapplication/pdf
dc.format1-7
dc.languageen
dc.relationJournal of Computer Science & Technology
dc.relationvol. 10, no. 1
dc.rightshttp://creativecommons.org/licenses/by-nc/3.0/
dc.rightsCreative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.subjectCiencias Informáticas
dc.titleA new AntTree-based algorithm for clustering short-text corpora
dc.typeArticulo
dc.typeArticulo


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