A tabu search based algorithm for clustering categorical data sets

Joyce C. Wong; Michael K. Ng

doi:10.1007/3-540-44491-2_81

A tabu search based algorithm for clustering categorical data sets

Joyce C. Wong, Michael K. Ng

Department of Mathematics

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

1 Citation (Scopus)

Abstract

Clustering methods partition a set of objects into clusters such that objects in the same cluster are more similar to each other than objects in different clusters according to some defined criteria. In this paper, we present an algorithm, called tabu search fuzzy k-modes, to extend the fuzzy k-means paradigm to categorical domains. Using the tabu search based technique, our algorithm can explore the solution space beyond local optimality in order to aim at finding a global optimal solution of the fuzzy clustering problem. It is found that our algorithm performs better, in terms of accuracy, than the fuzzy k-modes algorithm.

Original language	English
Title of host publication	Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents
Subtitle of host publication	Second International Conference Shatin, N.T., Hong Kong, China, December 13-15, 2000. Proceedings
Editors	Kwong Sak Leung, Lai-Wan Chan, Helen Meng
Publisher	Springer Berlin Heidelberg
Pages	559-564
Number of pages	6
Edition	1st
ISBN (Electronic)	9783540444916
ISBN (Print)	3540414509, 9783540414506
DOIs	https://doi.org/10.1007/3-540-44491-2_81
Publication status	Published - 29 Nov 2000
Event	2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000 - Hong Kong, Hong Kong Duration: 13 Dec 2000 → 15 Dec 2000 https://link.springer.com/book/10.1007/3-540-44491-2 (Conference Proceedings)

Publication series

Name	Lecture Notes in Computer Science
Volume	1983
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000
Country/Territory	Hong Kong
City	Hong Kong
Period	13/12/00 → 15/12/00
Internet address	https://link.springer.com/book/10.1007/3-540-44491-2 (Conference Proceedings)

Scopus Subject Areas

Theoretical Computer Science
General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/3-540-44491-2_81

Cite this

Wong, J. C., & Ng, M. K. (2000). A tabu search based algorithm for clustering categorical data sets. In K. S. Leung, L.-W. Chan, & H. Meng (Eds.), Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents: Second International Conference Shatin, N.T., Hong Kong, China, December 13-15, 2000. Proceedings (1st ed., pp. 559-564). (Lecture Notes in Computer Science; Vol. 1983). Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-44491-2_81

Wong, Joyce C. ; Ng, Michael K. / A tabu search based algorithm for clustering categorical data sets. Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents: Second International Conference Shatin, N.T., Hong Kong, China, December 13-15, 2000. Proceedings. editor / Kwong Sak Leung ; Lai-Wan Chan ; Helen Meng. 1st. ed. Springer Berlin Heidelberg, 2000. pp. 559-564 (Lecture Notes in Computer Science).

@inproceedings{00bfafa9144f49bba569dd453e41d525,

title = "A tabu search based algorithm for clustering categorical data sets",

abstract = "Clustering methods partition a set of objects into clusters such that objects in the same cluster are more similar to each other than objects in different clusters according to some defined criteria. In this paper, we present an algorithm, called tabu search fuzzy k-modes, to extend the fuzzy k-means paradigm to categorical domains. Using the tabu search based technique, our algorithm can explore the solution space beyond local optimality in order to aim at finding a global optimal solution of the fuzzy clustering problem. It is found that our algorithm performs better, in terms of accuracy, than the fuzzy k-modes algorithm.",

author = "Wong, {Joyce C.} and Ng, {Michael K.}",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2000.; 2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000 ; Conference date: 13-12-2000 Through 15-12-2000",

year = "2000",

month = nov,

day = "29",

doi = "10.1007/3-540-44491-2_81",

language = "English",

isbn = "3540414509",

series = "Lecture Notes in Computer Science",

publisher = "Springer Berlin Heidelberg",

pages = "559--564",

editor = "Leung, {Kwong Sak} and Lai-Wan Chan and Helen Meng",

booktitle = "Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents",

edition = "1st",

url = "https://link.springer.com/book/10.1007/3-540-44491-2",

}

Wong, JC & Ng, MK 2000, A tabu search based algorithm for clustering categorical data sets. in KS Leung, L-W Chan & H Meng (eds), Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents: Second International Conference Shatin, N.T., Hong Kong, China, December 13-15, 2000. Proceedings. 1st edn, Lecture Notes in Computer Science, vol. 1983, Springer Berlin Heidelberg, pp. 559-564, 2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000, Hong Kong, Hong Kong, 13/12/00. https://doi.org/10.1007/3-540-44491-2_81

A tabu search based algorithm for clustering categorical data sets. / Wong, Joyce C.; Ng, Michael K.
Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents: Second International Conference Shatin, N.T., Hong Kong, China, December 13-15, 2000. Proceedings. ed. / Kwong Sak Leung; Lai-Wan Chan; Helen Meng. 1st. ed. Springer Berlin Heidelberg, 2000. p. 559-564 (Lecture Notes in Computer Science; Vol. 1983).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - A tabu search based algorithm for clustering categorical data sets

AU - Wong, Joyce C.

AU - Ng, Michael K.

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2000.

PY - 2000/11/29

Y1 - 2000/11/29

N2 - Clustering methods partition a set of objects into clusters such that objects in the same cluster are more similar to each other than objects in different clusters according to some defined criteria. In this paper, we present an algorithm, called tabu search fuzzy k-modes, to extend the fuzzy k-means paradigm to categorical domains. Using the tabu search based technique, our algorithm can explore the solution space beyond local optimality in order to aim at finding a global optimal solution of the fuzzy clustering problem. It is found that our algorithm performs better, in terms of accuracy, than the fuzzy k-modes algorithm.

AB - Clustering methods partition a set of objects into clusters such that objects in the same cluster are more similar to each other than objects in different clusters according to some defined criteria. In this paper, we present an algorithm, called tabu search fuzzy k-modes, to extend the fuzzy k-means paradigm to categorical domains. Using the tabu search based technique, our algorithm can explore the solution space beyond local optimality in order to aim at finding a global optimal solution of the fuzzy clustering problem. It is found that our algorithm performs better, in terms of accuracy, than the fuzzy k-modes algorithm.

UR - http://www.scopus.com/inward/record.url?scp=84929002804&partnerID=8YFLogxK

UR - https://link.springer.com/chapter/10.1007/3-540-44491-2_81

U2 - 10.1007/3-540-44491-2_81

DO - 10.1007/3-540-44491-2_81

M3 - Conference proceeding

AN - SCOPUS:84929002804

SN - 3540414509

SN - 9783540414506

T3 - Lecture Notes in Computer Science

SP - 559

EP - 564

BT - Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents

A2 - Leung, Kwong Sak

A2 - Chan, Lai-Wan

A2 - Meng, Helen

PB - Springer Berlin Heidelberg

T2 - 2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000

Y2 - 13 December 2000 through 15 December 2000

ER -

Wong JC, Ng MK. A tabu search based algorithm for clustering categorical data sets. In Leung KS, Chan LW, Meng H, editors, Intelligent Data Engineering and Automated Learning - IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents: Second International Conference Shatin, N.T., Hong Kong, China, December 13-15, 2000. Proceedings. 1st ed. Springer Berlin Heidelberg. 2000. p. 559-564. (Lecture Notes in Computer Science). doi: 10.1007/3-540-44491-2_81

A tabu search based algorithm for clustering categorical data sets

Abstract

Publication series

Conference

Scopus Subject Areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this