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Volumn 3100, Issue , 2004, Pages 59-77

Learning rules from very large databases using rough multisets

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Indexed keywords


EID: 35048884544     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-27794-1_2     Document Type: Article
Times cited : (12)

References (22)
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    • Sarawagi, S., S. Thomas, and R. Agrawal, "Integrating association rule mining with relational database systems: alternatives and implications," Data Mining and Knowledge Discovery, 4, 89-125, (2000).
    • (2000) Data Mining and Knowledge Discovery , vol.4 , pp. 89-125
    • Sarawagi, S.1    Thomas, S.2    Agrawal, R.3
  • 3
    • 84896749974 scopus 로고    scopus 로고
    • Scalable mining for classification rules in relational databases
    • Wang, M., B. Iyer, and J.S. Vitter, "Scalable mining for classification rules in relational databases," IDEAS, 58-67, (1998).
    • (1998) IDEAS , pp. 58-67
    • Wang, M.1    Iyer, B.2    Vitter, J.S.3
  • 8
    • 84986140419 scopus 로고
    • Rough sets and decision tables
    • Berlin, Heidelberg, Springer-Verlag
    • Pawlak, Z., "Rough sets and decision tables," Lecture Notes in Computer Science 208, 186-196, Berlin, Heidelberg, Springer-Verlag, (1985).
    • (1985) Lecture Notes in Computer Science , vol.208 , pp. 186-196
    • Pawlak, Z.1
  • 13
    • 0002580328 scopus 로고
    • From rough set theory to evidence theory
    • edited by R. R. Yager, J. Kacprzyk, and M. Fedrizzi, John Wiley & Sons, Inc. New York
    • Skowron, A. and J. Grzymala-Busse, "From rough set theory to evidence theory." in Advances in the Dempster-Shafer Theory of Evidence, edited by R. R. Yager, J. Kacprzyk, and M. Fedrizzi, 193-236, John Wiley & Sons, Inc. New York, (1994).
    • (1994) Advances in the Dempster-Shafer Theory of Evidence , pp. 193-236
    • Skowron, A.1    Grzymala-Busse, J.2
  • 16
    • 0001905486 scopus 로고
    • Knowledge acquisition under uncertainty: A rough set approach
    • Grzymala-Busse, J.W., "Knowledge acquisition under uncertainty: a rough set approach," J. of Intelligent and Robotic Systems, Vol. 1, 3-16, (1988).
    • (1988) J. of Intelligent and Robotic Systems , vol.1 , pp. 3-16
    • Grzymala-Busse, J.W.1
  • 17
    • 0040204986 scopus 로고
    • Incremental learning of production rules from examples under uncertainty: A rough set approach
    • Chan, C.-C., "Incremental learning of production rules from examples under uncertainty: a rough set approach," Int. J. of Software Engineering and Knowledge Engineering, Vol. 1, No. 4, 439-461, (1991).
    • (1991) Int. J. of Software Engineering and Knowledge Engineering , vol.1 , Issue.4 , pp. 439-461
    • Chan, C.-C.1
  • 19
    • 51149088627 scopus 로고    scopus 로고
    • Bitmap techniques for optimizing decision support queries and association rule algorithms
    • Hu, X., T.Y. Lin, E. Louie, "Bitmap techniques for optimizing decision support queries and association rule algorithms," IDEAS, (2003), pp. 3443.
    • (2003) IDEAS , pp. 3443
    • Hu, X.1    Lin, T.Y.2    Louie, E.3
  • 20
    • 16244367061 scopus 로고    scopus 로고
    • Rough Set Approach to Rules Generation from Incomplete Information Systems
    • Marcel Dekker, Inc., New York
    • Kryszkiewicz, M., "Rough Set Approach to Rules Generation from Incomplete Information Systems," In The Encyclopedia of Computer Science and Technology, Marcel Dekker, Inc., New York, Vol. 44, 319-346, (2001).
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    • Kryszkiewicz, M.1
  • 21
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    • Various approaches to reasoning with frequency based decision reducts: A survey
    • L. Polkowski, S. Tsumoto, T.Y. Lin (eds.), Physica-Verlag, Heidelberg, New York
    • Ślçzak, D., "Various approaches to reasoning with frequency based decision reducts: a survey," in Rough Set Methods and Applications, L. Polkowski, S. Tsumoto, T.Y. Lin (eds.), Physica-Verlag, Heidelberg, New York, (2000).
    • (2000) Rough Set Methods and Applications
    • Ślçzak, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.