A new AntTree-based algorithm for clustering short-text corpora


  • Marcelo Luis Errecalde Development and Research Laboratory in Computacional Intelligence (LIDIC), Universidad Nacional de San Luis, San Luis, Argentina
  • Diego Alejandro Ingaramo Development and Research Laboratory in Computacional Intelligence (LIDIC), Universidad Nacional de San Luis, San Luis, Argentina
  • Paolo Rosso Natural Language Engineering Lab.,ELiRF, Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain


internal validity measures, AntTree, Short-text clustering, Bio-inspired algorithms, Internal Validity Measures, Silhouette Coefficient


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.


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How to Cite

Errecalde, M. L., Ingaramo, D. A., & Rosso, P. (2010). A new AntTree-based algorithm for clustering short-text corpora. Journal of Computer Science and Technology, 10(01), p. 1–7. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/708



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