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
