Feature Selection And Enhanced Krill Herd Algorithm For Text Document Clustering

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 selecti...

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Bibliographic Details
Main Author: Abualigah, Laith Mohammad Qasim
Format: Thesis
Language:English
Published: 2018
Subjects:
Online Access:http://eprints.usm.my/43662/1/LAITH%20MOHAMMAD%20QASIM%20ABUALIGAH.pdf
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Summary: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.