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Empirical Study on Unsupervised Feature Selection for Document Clustering
Aušra Mackutė-Varoneckienė, Tomas Krilavičius
107 - 110
10.3233/978-1-61499-442-8-107
Frontiers in Artificial Intelligence and Applications
Volume 268: Human Language Technologies – The Baltic Perspective
Abstract

Unsupervised feature selection is very important in the document clustering process. This paper presents the empirical research on feature selection as well as clustering methods and feature representation suitability for Lithuanian and Russian document clustering.

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