Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering

Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering
Author :
Publisher : Springer
Total Pages : 186
Release :
ISBN-10 : 9783030106744
ISBN-13 : 3030106748
Rating : 4/5 (44 Downloads)

Book Synopsis Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering by : Laith Mohammad Qasim Abualigah

Download or read book Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering written by Laith Mohammad Qasim Abualigah and published by Springer. This book was released on 2018-12-18 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book puts forward a new method for solving the text document (TD) clustering problem, which is established in two main stages: (i) A new feature selection method based on a particle swarm optimization algorithm with a novel weighting scheme is proposed, as well as a detailed dimension reduction technique, in order to obtain a new subset of more informative features with low-dimensional space. This new subset is subsequently used to improve the performance of the text clustering (TC) algorithm and reduce its computation time. The k-mean clustering algorithm is used to evaluate the effectiveness of the obtained subsets. (ii) Four krill herd algorithms (KHAs), namely, the (a) basic KHA, (b) modified KHA, (c) hybrid KHA, and (d) multi-objective hybrid KHA, are proposed to solve the TC problem; each algorithm represents an incremental improvement on its predecessor. For the evaluation process, seven benchmark text datasets are used with different characterizations and complexities. Text document (TD) clustering is a new trend in text mining in which the TDs are separated into several coherent clusters, where all documents in the same cluster are similar. The findings presented here confirm that the proposed methods and algorithms delivered the best results in comparison with other, similar methods to be found in the literature.


Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering Related Books

Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering
Language: en
Pages: 186
Authors: Laith Mohammad Qasim Abualigah
Categories: Technology & Engineering
Type: BOOK - Published: 2018-12-18 - Publisher: Springer

DOWNLOAD EBOOK

This book puts forward a new method for solving the text document (TD) clustering problem, which is established in two main stages: (i) A new feature selection
Recent Advances in Hybrid Metaheuristics for Data Clustering
Language: en
Pages: 196
Authors: Sourav De
Categories: Computers
Type: BOOK - Published: 2020-08-24 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques Rec
Metaheuristics in Machine Learning: Theory and Applications
Language: en
Pages: 765
Authors: Diego Oliva
Categories: Computational intelligence
Type: BOOK - Published: - Publisher: Springer Nature

DOWNLOAD EBOOK

This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolut
Comprehensive Metaheuristics
Language: en
Pages: 468
Authors: Seyedali Mirjalili
Categories: Computers
Type: BOOK - Published: 2023-01-31 - Publisher: Elsevier

DOWNLOAD EBOOK

Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-wor
Advanced Applications of NLP and Deep Learning in Social Media Data
Language: en
Pages: 325
Authors: Abd El-Latif, Ahmed A.
Categories: Computers
Type: BOOK - Published: 2023-06-05 - Publisher: IGI Global

DOWNLOAD EBOOK

Social media platforms are one of the main generators of textual data where people around the world share their daily life experiences and information with onli