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CICLING
2008
Springer

Evaluation of Internal Validity Measures in Short-Text Corpora

8 years 4 months ago
Evaluation of Internal Validity Measures in Short-Text Corpora
Short texts clustering is one of the most difficult tasks in natural language processing due to the low frequencies of the document terms. We are interested in analysing these kind of corpora in order to develop novel techniques that may be used to improve results obtained by classical clustering algorithms. In this paper we are presenting an evaluation of different internal clustering validity measures in order to determine the possible correlation between these measures and that of the F-Measure, a well-known external clustering measure used to calculate the performance of clustering algorithms. We have used several short-text corpora in the experiments carried out. The obtained correlation with a particular set of internal validity measures let us to conclude that some of them may be used to improve the performance of text clustering algorithms.
Diego Ingaramo, David Pinto, Paolo Rosso, Marcelo
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where CICLING
Authors Diego Ingaramo, David Pinto, Paolo Rosso, Marcelo Errecalde
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