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Volumn 41, Issue 4, 2000, Pages 433-447

Building knowledge scouts using KGL metalanguage

Author keywords

Association graphs; Attributional calculus; Data mining; Inductive databases; Knowledge discovery; Knowledge generation language; Knowledge scouts; Knowledge visualization

Indexed keywords


EID: 0039770011     PISSN: 01692968     EISSN: None     Source Type: Journal    
DOI: 10.3233/fi-2000-41404     Document Type: Article
Times cited : (3)

References (20)
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    • Bergadano, F.1    Matwin, S.2    Michalski, R.S.3    Zhang, J.4
  • 3
    • 0004974847 scopus 로고
    • University of Colorado Behavioral Research Institute, Boulder, CO, 1977, distributed by Inter-University Consortium for Political and Social Research, Ann Arbor, MI
    • Elliott, D., "National Youth Survey (United States), Wave I, 1976", [Computer file]. ICPSR version, University of Colorado Behavioral Research Institute, Boulder, CO, 1977, distributed by Inter-University Consortium for Political and Social Research, Ann Arbor, MI, 1994.
    • (1994) "National Youth Survey (United States), Wave I, 1976", [Computer File]. ICPSR Version
    • Elliott, D.1
  • 5
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    • A description and user's guide for CLUSTER/2C++ a program for conjunctive conceptual clustering
    • MLI 97-10, George Mason University, Fairfax, VA
    • Fischthal, S., "A Description and User's Guide for CLUSTER/2C++ A Program for Conjunctive Conceptual Clustering", Reports of the Machine Learning and Inference Laboratory, MLI 97-10, George Mason University, Fairfax, VA, 1997.
    • (1997) Reports of the Machine Learning and Inference Laboratory
    • Fischthal, S.1
  • 10
    • 0039213481 scopus 로고    scopus 로고
    • Selecting examples for partial memory learning
    • Maloof, M. and Michalski, R.S., "Selecting Examples for Partial Memory Learning", Machine Learning, Vol. 30, pp. 1-22, 1998.
    • (1998) Machine Learning , vol.30 , pp. 1-22
    • Maloof, M.1    Michalski, R.S.2
  • 12
    • 0003046840 scopus 로고
    • A theory and methodology of inductive learning
    • Michalski, R.S. Carbonell, J.G. and Mitchell, T.M. (eds.), Palo Alto: Tioga Publishing
    • Michalski, R.S., "A Theory and Methodology of Inductive Learning", In Michalski, R.S. Carbonell, J.G. and Mitchell, T.M. (eds.), Machine Learning: An Artificial Intelligence Approach, Palo Alto: Tioga Publishing, pp. 83-129, 1983.
    • (1983) Machine Learning: An Artificial Intelligence Approach , pp. 83-129
    • Michalski, R.S.1
  • 13
    • 0031165377 scopus 로고    scopus 로고
    • Seeking knowledge in the deluge of facts
    • Michalski, R.S., "Seeking Knowledge in the Deluge of Facts", Fundamenta Informaticae, Vol. 30, pp. 283-297, 1997.
    • (1997) Fundamenta Informaticae , vol.30 , pp. 283-297
    • Michalski, R.S.1
  • 14
    • 0005107221 scopus 로고    scopus 로고
    • Natural induction: Theory, methodology and applications to machine learning and knowledge mining
    • George Mason University, to appear
    • Michalski, R.S., "NATURAL INDUCTION: Theory, Methodology and Applications to Machine Learning and Knowledge Mining", Reports of the Machine Learning and Inference Laboratory, George Mason University, to appear.
    • Reports of the Machine Learning and Inference Laboratory
    • Michalski, R.S.1
  • 15
    • 0001214429 scopus 로고    scopus 로고
    • Data mining and knowledge discovery: A review of issues and multistrategy methodology
    • Michalski, R.S., Bratko, I. and Kubat, M. (eds.), London, John Wiley and Sons
    • Michalski R. S. and Kaufman, K., "Data Mining and Knowledge Discovery: A Review of Issues and Multistrategy Methodology", in Michalski, R.S., Bratko, I. and Kubat, M. (eds.), Machine Learning and Data Mining: Methods and Applications, London, John Wiley and Sons pp. 71-112, 1998.
    • (1998) Machine Learning and Data Mining: Methods and Applications , pp. 71-112
    • Michalski, R.S.1    Kaufman, K.2
  • 16
    • 0020783239 scopus 로고
    • Automated construction of classifications: Conceptual clustering versus numerical taxonomy
    • July
    • Michalski, R.S. and Stepp, R., "Automated Construction of Classifications: Conceptual Clustering versus Numerical Taxonomy", IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. PAMI-5, No. 4, pp. 396-410, July, 1983.
    • (1983) IEEE Trans. on Pattern Analysis and Machine Intelligence , vol.PAMI-5 , Issue.4 , pp. 396-410
    • Michalski, R.S.1    Stepp, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.