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Text Document Clustering Using Memetic Feature Selection

Authors:

Ibraheem Al-Jadir,

Hong XieAuthors Info & Claims

ICMLC '17: Proceedings of the 9th International Conference on Machine Learning and Computing

Pages 415 - 420

https://doi.org/10.1145/3055635.3056603

Published: 24 February 2017 Publication History

Abstract

With the wide increase of the volume of electronic documents, it becomes inevitable the need to invent more sophisticated machine learning methods to manage the issue. In this paper, a Memetic feature selection technique is proposed to improve the k-means and the spherical k-means clustering algorithms. The proposed Memetic feature selection technique combines the wrapper inductive method with the filter ranking method. The internal and external clustering evaluation measures are used to assess the resulted clusters. The test results showed that after using the proposed hybrid method, the resulted clusters were more accurate and more compacted in comparison to the clusters resulted from using the GA-selected feature or using the entire feature space.

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Cited By

Al-Jadir IWong KFung CXie H(2020)Unsupervised Text Feature Selection Using Memetic Dichotomous Differential EvolutionAlgorithms10.3390/a1306013113:6(131)Online publication date: 26-May-2020
https://doi.org/10.3390/a13060131
Abualigah LHanandeh EKhader AOtair MShandilya S(2020)An Improved B-hill Climbing Optimization Technique for Solving the Text Documents Clustering ProblemCurrent Medical Imaging Formerly Current Medical Imaging Reviews10.2174/157340561466618090311254116:4(296-306)Online publication date: 7-May-2020
https://doi.org/10.2174/1573405614666180903112541
A CG M(2019)An Enhanced Method for Topic Modeling using Concept-Latent2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon)10.1109/COMITCon.2019.8862179(485-490)Online publication date: Feb-2019
https://doi.org/10.1109/COMITCon.2019.8862179
Show More Cited By

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cover image ACM Other conferences

ICMLC '17: Proceedings of the 9th International Conference on Machine Learning and Computing

February 2017

545 pages

ISBN:9781450348171

DOI:10.1145/3055635

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Southwest Jiaotong University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 February 2017

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ICMLC 2017

ICMLC 2017: 2017 the 9th International Conference on Machine Learning and Computing

February 24 - 26, 2017

Singapore, Singapore

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Cited By

Al-Jadir IWong KFung CXie H(2020)Unsupervised Text Feature Selection Using Memetic Dichotomous Differential EvolutionAlgorithms10.3390/a1306013113:6(131)Online publication date: 26-May-2020
https://doi.org/10.3390/a13060131
Abualigah LHanandeh EKhader AOtair MShandilya S(2020)An Improved B-hill Climbing Optimization Technique for Solving the Text Documents Clustering ProblemCurrent Medical Imaging Formerly Current Medical Imaging Reviews10.2174/157340561466618090311254116:4(296-306)Online publication date: 7-May-2020
https://doi.org/10.2174/1573405614666180903112541
A CG M(2019)An Enhanced Method for Topic Modeling using Concept-Latent2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon)10.1109/COMITCon.2019.8862179(485-490)Online publication date: Feb-2019
https://doi.org/10.1109/COMITCon.2019.8862179
Moscato PMathieson L(2019)Memetic Algorithms for Business Analytics and Data Science: A Brief SurveyBusiness and Consumer Analytics: New Ideas10.1007/978-3-030-06222-4_13(545-608)Online publication date: 31-May-2019
https://doi.org/10.1007/978-3-030-06222-4_13
Al-Jadir IWong KFung CXie H(2017)Text Dimensionality Reduction for Document Clustering Using Hybrid Memetic Feature SelectionMulti-disciplinary Trends in Artificial Intelligence10.1007/978-3-319-69456-6_23(281-289)Online publication date: 19-Oct-2017
https://doi.org/10.1007/978-3-319-69456-6_23

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