A logical approach to fuzzy data analysis

Churn Jung Liau; Duen-Ren Liu

doi:10.1007/978-3-540-48247-5_51

A logical approach to fuzzy data analysis

Churn Jung Liau, Duen-Ren Liu

National Chiao Tung University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

In this paper, we investigate the extraction of fuzzy rules from data tables based on possibility theory. A possibilistic decision language is used to represent the extracted fuzzy rules. The algorithm for rule extraction is presented and the complexity analysis is carried out. Since the results of the rule induction process strongly depend on the representation language, we also discuss some approach for dynamic adjustment of the language based on the data.

Original language	English
Title of host publication	Principles of Data Mining and Knowledge Discovery - 3d European Conference, PKDD 1999, Proceedings
Editors	Jan Rauch, Jan M. Żytkow
Publisher	Springer Verlag
Pages	412-417
Number of pages	6
ISBN (Print)	3540664904, 9783540664901
DOIs	https://doi.org/10.1007/978-3-540-48247-5_51
State	Published - 1 Jan 1999
Event	3rd European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 1999 - Prague, Czech Republic Duration: 15 Sep 1999 → 18 Sep 1999

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1704
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 1999
Country	Czech Republic
City	Prague
Period	15/09/99 → 18/09/99

Access to Document

10.1007/978-3-540-48247-5_51

Link to publication in Scopus

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Liau, C. J., & Liu, D-R. (1999). A logical approach to fuzzy data analysis. In J. Rauch, & J. M. Żytkow (Eds.), Principles of Data Mining and Knowledge Discovery - 3d European Conference, PKDD 1999, Proceedings (pp. 412-417). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1704). Springer Verlag. https://doi.org/10.1007/978-3-540-48247-5_51

Liau, Churn Jung ; Liu, Duen-Ren. / A logical approach to fuzzy data analysis. Principles of Data Mining and Knowledge Discovery - 3d European Conference, PKDD 1999, Proceedings. editor / Jan Rauch ; Jan M. Żytkow. Springer Verlag, 1999. pp. 412-417 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Liau, CJ & Liu, D-R 1999, A logical approach to fuzzy data analysis. in J Rauch & JM Żytkow (eds), Principles of Data Mining and Knowledge Discovery - 3d European Conference, PKDD 1999, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1704, Springer Verlag, pp. 412-417, 3rd European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 1999, Prague, Czech Republic, 15/09/99. https://doi.org/10.1007/978-3-540-48247-5_51

A logical approach to fuzzy data analysis. / Liau, Churn Jung; Liu, Duen-Ren.

Principles of Data Mining and Knowledge Discovery - 3d European Conference, PKDD 1999, Proceedings. ed. / Jan Rauch; Jan M. Żytkow. Springer Verlag, 1999. p. 412-417 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1704).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Liau CJ, Liu D-R. A logical approach to fuzzy data analysis. In Rauch J, Żytkow JM, editors, Principles of Data Mining and Knowledge Discovery - 3d European Conference, PKDD 1999, Proceedings. Springer Verlag. 1999. p. 412-417. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-48247-5_51