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Volumn 4, Issue 3-4, 2000, Pages 289-304

Knowledge acquisition from quantitative data using the rough-set theory

Author keywords

certain rule; data mining; fuzzy set; knowledge acquisition; possible rule; quantitative value; rough set

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA MINING; DECISION SUPPORT SYSTEMS; EXPERT SYSTEMS; FUZZY SET THEORY; FUZZY SETS; KNOWLEDGE ACQUISITION; LINGUISTICS; MEMBERSHIP FUNCTIONS;

EID: 0000742181     PISSN: 1088467X     EISSN: 15714128     Source Type: Journal    
DOI: 10.3233/ida-2000-43-409     Document Type: Article
Times cited : (26)

References (27)
  • 2
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    • (1998) Journal of Information Sciences , vol.107 , pp. 169-176
    • Chan, C.C.1
  • 6
    • 0001905486 scopus 로고
    • Knowledge acquisition under uncertainty: A rough set approach
    • J.W. Grzymala-Busse, Knowledge acquisition under uncertainty: A rough set approach, Journal of Intelligent Robotic Systems 1 (1988), 3-16.
    • (1988) Journal of Intelligent Robotic Systems , vol.1 , pp. 3-16
    • Grzymala-Busse, J.W.1
  • 7
    • 84883705705 scopus 로고    scopus 로고
    • Mining association rules from quantitative data, accepted and to appear in Intelligent Data Analysis
    • T.P. Hong, C.S. Kuo and S.C. Chi, Mining association rules from quantitative data, accepted and to appear in Intelligent Data Analysis: An International Journal.
    • An International Journal
    • Hong, T.P.1    Kuo, C.S.2    Chi, S.C.3
  • 8
    • 0033130756 scopus 로고    scopus 로고
    • Finding relevant attributes and membership functions
    • T.P. Hong and J.B. Chen, Finding relevant attributes and membership functions, Fuzzy Sets and Systems 103(3) (1999), 389-404.
    • (1999) Fuzzy Sets and Systems , vol.103 , Issue.3 , pp. 389-404
    • Hong, T.P.1    Chen, J.B.2
  • 9
    • 0030289773 scopus 로고    scopus 로고
    • Induction of fuzzy rules and membership functions from training examples
    • T.P. Hong and C.Y. Lee, Induction of fuzzy rules and membership functions from training examples, Fuzzy Sets and Systems 84 (1996), 33-47.
    • (1996) Fuzzy Sets and Systems , vol.84 , pp. 33-47
    • Hong, T.P.1    Lee, C.Y.2
  • 10
    • 0031094448 scopus 로고    scopus 로고
    • Ageneralized version space learning algorithm for noisy and uncertain data
    • T.P. Hong and S.S. Tseng, Ageneralized version space learning algorithm for noisy and uncertain data, IEEE Transactions on Knowledge and Data Engineering 9(2) (1997), 336-340.
    • (1997) IEEE Transactions on Knowledge and Data Engineering , vol.9 , Issue.2 , pp. 336-340
    • Hong, T.P.1    Tseng, S.S.2
  • 17
    • 0002265912 scopus 로고    scopus 로고
    • Reasoning with incomplete information: Rough set based information logics
    • V. Alagar, S. Bergler and F.Q. Dong, eds Springer
    • E. Orlowska, Reasoning with incomplete information: rough set based information logics, in: Incompleteness and Uncertainty in Information Systems, V. Alagar, S. Bergler and F.Q. Dong, eds., Springer, pp. 16-33.
    • Incompleteness and Uncertainty in Information Systems , pp. 16-33
    • Orlowska, E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.