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Volumn 1, Issue , 1999, Pages 264-269

Adaptive web sites: Conceptual cluster mining

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE WEB SITES; AUTOMATIC CREATIONS; CONCEPT DESCRIPTION LANGUAGE; CONCEPTUAL CLUSTERING; CONCEPTUAL CLUSTERS; EXPERIMENTAL EVIDENCE; STATISTICAL CLUSTERING; USER INTERFACE DESIGNS;

EID: 84880677668     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (65)

References (17)
  • 2
    • 0025419775 scopus 로고
    • Singular extensions. Adding selectivity to brute-force searching
    • DOI 10.1016/0004-3702(90)90073-9
    • T. Anantharaman, M. Campbell, and F. Hsu. Singular extensions: adding selectivity to brute-force searching. Artificial Intelligence, 43(1):99-109, 1990. (Pubitemid 20717238)
    • (1990) Artificial Intelligence , vol.43 , Issue.1 , pp. 99-109
    • Anantharaman, T.1    Campbell, M.S.2    Hsu F.-hsiung3
  • 4
    • 0343442766 scopus 로고
    • Knowledge Acquisition Via Incremental Conceptual Clustering
    • D. Fisher. Knowledge Acquisition Via Incremental Conceptual Clustering. Machine Learning, 2:139-172, 1987.
    • (1987) Machine Learning , vol.2 , pp. 139-172
    • Fisher, D.1
  • 5
    • 0000783818 scopus 로고
    • Conceptual Clustering, Categorization, and Polymorphy
    • S. Hanson and M. Bauer. Conceptual Clustering, Categorization, and Polymorphy. Machine Learning, 3:343-372, 1989.
    • (1989) Machine Learning , vol.3 , pp. 343-372
    • Hanson, S.1    Bauer, M.2
  • 7
    • 0025389210 scopus 로고
    • Boolean feature discovery in empirical learning
    • G. Pagallo and D. Haussler. Boolean feature discovery in empirical learning. Machine Learning, 5:71-100, 1990.
    • (1990) Machine Learning , vol.5 , pp. 71-100
    • Pagallo, G.1    Haussler, D.2
  • 10
    • 0024627518 scopus 로고
    • Inferring decision trees using the minimum description length principle
    • J. R. Quinlan and R. L. Rivest. Inferring decision trees using the minimum description length principle. Information and Computation, 80:227-248, 1989.
    • (1989) Information and Computation , vol.80 , pp. 227-248
    • Quinlan, J.R.1    Rivest, R.L.2
  • 11
    • 0000019005 scopus 로고
    • Clustering algorithms
    • W.B. Frakes and R. Baeza-Yates, editors, Prentice Hall, Eaglewood Cliffs, N.J.
    • E. Rasmussen. Clustering algorithms. In W.B. Frakes and R. Baeza-Yates, editors, Information Retrieval, pages 419-442. Prentice Hall, Eaglewood Cliffs, N.J., 1992.
    • (1992) Information Retrieval , pp. 419-442
    • Rasmussen, E.1
  • 15
    • 0022906994 scopus 로고
    • Implementing agglomerative hierarchical clustering algorithms for use in document retrieval
    • E.M. Voorhees. Implementing agglomerative hierarchical clustering algorithms for use in document retrieval. Information Processing & Management, 22:465-476, 1986.
    • (1986) Information Processing & Management , vol.22 , pp. 465-476
    • Voorhees, E.M.1
  • 16
    • 3543147086 scopus 로고
    • Recent trends in hierarchical document clustering: A critical review
    • P. Willet. Recent trends in hierarchical document clustering: a critical review. Information Processing and Management, 24:577-97, 1988.
    • (1988) Information Processing and Management , vol.24 , pp. 577-597
    • Willet, P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.