Abualigah, Laith Mohammad Qasim
(2018)
Feature Selection And Enhanced Krill Herd Algorithm For Text Document Clustering.
PhD thesis, Universiti Sains Malaysia.
Abstract
Text document (TD) clustering is a new trend in text mining in which the TDs are separated into several coherent clusters, where documents in the same cluster are
similar. In this study, a new method for solving the TD clustering problem worked in the following two stages: (i) A new feature selection method using particle swarm
optimization algorithm with a novel weighting scheme and a detailed dimension reduction technique are proposed to obtain a new subset of more informative features with low-dimensional space.
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