Singular Value Decomposition for dimensionality reduction in unsupervised text learning problems

Taufik Fuadi Abidin; Bustami Yusuf; Munzir Umran

doi:10.1109/ICETC.2010.5529649

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Singular Value Decomposition for dimensionality reduction in unsupervised text learning problems

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Taufik Fuadi Abidin, Bustami Yusuf, Munzir Umran

2010 ICETC 2010 - 2010 2nd International Conference on Education Technology and Computer Vol. 4 Article Cited by 15

Abstract

Partitioning vast amounts of text documents is a challenging problem due to a high dimensional representation of the documents. In this study, we investigate the quality of text document clustering when Singular Value Decomposition (SVD) is used to reduce the dimension of the documents. The results show that the quality of the clusters is very comparable to that of when the dimensions are not reduced. In addition, the computational cost to cluster documents can be reduced significantly when the clustering is done on a small dimension. © 2010 IEEE.

Affiliations

Mathematics Department, College of Mathematics and Natural Science, Syiah Kuala University, Banda Aceh, Indonesia

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