Apply rough set theory into the information extraction - The application of the clustering

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Clustering has always been an important subject in data mining, and it has been applied in various domains. Constrained clustering has been an emerging issue over the last few years. Its main idea is applying constraints to the process of clustering to decrease the running time and cost to expectantly promote the quality of clustering. Because clustering is a combinative optimization question, there are some problems such as NP-Hard work and deciding the number of clusters. This paper proposes a constrained clustering technique combining Rough Set theory and Genetic Algorithm into the clustering. We also developed the prototyping system and performed experiments to prove the effectiveness and compare it with other clustering techniques, such as Genetic Algorithm-based clustering and Self-organizing Maps. Finally, the results showed our approach is actually better than other methods.

Original languageEnglish
Title of host publicationNCM 2009 - 5th International Joint Conference on INC, IMS, and IDC
Pages262-266
Number of pages5
DOIs
Publication statusPublished - 2009 Dec 1
EventNCM 2009 - 5th International Joint Conference on Int. Conf. on Networked Computing, Int. Conf. on Advanced Information Management and Service, and Int. Conf. on Digital Content, Multimedia Technology and its Applications - Seoul, Korea, Republic of
Duration: 2009 Aug 252009 Aug 27

Publication series

NameNCM 2009 - 5th International Joint Conference on INC, IMS, and IDC

Other

OtherNCM 2009 - 5th International Joint Conference on Int. Conf. on Networked Computing, Int. Conf. on Advanced Information Management and Service, and Int. Conf. on Digital Content, Multimedia Technology and its Applications
CountryKorea, Republic of
CitySeoul
Period09-08-2509-08-27

Fingerprint

Rough set theory
Genetic algorithms
Self organizing maps
Data mining
Costs
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Software

Cite this

Liang, W. Y. (2009). Apply rough set theory into the information extraction - The application of the clustering. In NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC (pp. 262-266). [5331716] (NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC). https://doi.org/10.1109/NCM.2009.297
Liang, Wen Yau. / Apply rough set theory into the information extraction - The application of the clustering. NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC. 2009. pp. 262-266 (NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC).
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Liang, WY 2009, Apply rough set theory into the information extraction - The application of the clustering. in NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC., 5331716, NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC, pp. 262-266, NCM 2009 - 5th International Joint Conference on Int. Conf. on Networked Computing, Int. Conf. on Advanced Information Management and Service, and Int. Conf. on Digital Content, Multimedia Technology and its Applications, Seoul, Korea, Republic of, 09-08-25. https://doi.org/10.1109/NCM.2009.297

Apply rough set theory into the information extraction - The application of the clustering. / Liang, Wen Yau.

NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC. 2009. p. 262-266 5331716 (NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Liang WY. Apply rough set theory into the information extraction - The application of the clustering. In NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC. 2009. p. 262-266. 5331716. (NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC). https://doi.org/10.1109/NCM.2009.297