Document Clustering based on Genetic Algorithm using D-Individual

Lim Choen Choi; Soon Cheol Park

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

Document Clustering based on Genetic Algorithm using D-Individual

In Proceedings of the International Workshop on Semantic Interoperability - Volume 0ICAART, 111-118, 2011 , Rome, Italy

Authors: Lim Choen Choi and Soon Cheol Park

Affiliation: Chonbuk National University, Korea, Republic of

Keyword(s): document clustering, genetic algorithm, k-means, group-average, artificial intelligent

Abstract: Document clustering using genetic algorithm shows good performance. However the genetic algorithm has problem of performance degradation by premature convergence phenomenon. In this paper, we proposed the document clustering based on Genetic Algorithm using D-Individual (DIGA) to solve this problem. Genetic algorithm is based on the diversity of population and the capability to convergence. Success of genetic algorithm depends on these two factors. If we use these factors efficiently, we can get a better solution in reduced execution time. We apply DIGA to Reuter-21578 text collection and demonstrate the effect of our clustering algorithm. The results show that our DIGA has better performance than traditional clustering algorithms (K-means, Group Average and genetic algorithm) in various experiments.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 18.220.66.151

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

Choi, L. and Park, S. (2011). Document Clustering based on Genetic Algorithm using D-Individual . In Proceedings of the International Workshop on Semantic Interoperability (ICAART 2011) - IWSI; ISBN 978-989-8425-43-0, SciTePress, pages 111-118. DOI: 10.5220/0003351601110118

@conference{iwsi11,
author={Lim Choen Choi. and Soon Cheol Park.},
title={Document Clustering based on Genetic Algorithm using D-Individual },
booktitle={Proceedings of the International Workshop on Semantic Interoperability (ICAART 2011) - IWSI},
year={2011},
pages={111-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003351601110118},
isbn={978-989-8425-43-0},
}

TY - CONF

JO - Proceedings of the International Workshop on Semantic Interoperability (ICAART 2011) - IWSI
TI - Document Clustering based on Genetic Algorithm using D-Individual
SN - 978-989-8425-43-0
AU - Choi, L.
AU - Park, S.
PY - 2011
SP - 111
EP - 118
DO - 10.5220/0003351601110118
PB - SciTePress