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Volumn , Issue , 2004, Pages 210-217

Learning to cluster web search results

Author keywords

Document clustering; Regression analysis; Search result organization

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); CORRELATION METHODS; LEARNING SYSTEMS; REGRESSION ANALYSIS; VOCABULARY CONTROL; WORLD WIDE WEB;

EID: 8644273327     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1008992.1009030     Document Type: Conference Paper
Times cited : (476)

References (17)
  • 7
    • 0002714543 scopus 로고    scopus 로고
    • Making large-scale SVM learning practical
    • Schölkopf B. and Surges C. and Smola A. (ed.), MIT-Press
    • Joachims T., Making large-Scale SVM Learning Practical. Advances in Kernel Methods - Support Vector Learning. Schölkopf B. and Surges C. and Smola A. (ed.), MIT-Press, 1999.
    • (1999) Advances in Kernel Methods - Support Vector Learning
    • Joachims, T.1
  • 10
    • 0010279648 scopus 로고    scopus 로고
    • An evaluation of techniques for clustering search results
    • Department of Computer Science, University of Massachusetts, Amherst
    • Leouski A. V. and Croft W. B. An Evaluation of Techniques for Clustering Search Results. Technical Report IR-76, Department of Computer Science, University of Massachusetts, Amherst, 1996.
    • (1996) Technical Report , vol.IR-76
    • Leouski, A.V.1    Croft, W.B.2
  • 11
    • 0010254378 scopus 로고    scopus 로고
    • Improving interactive retrieval by combining ranked list and clustering
    • College de France
    • Leuski A. and Allan J. Improving Interactive Retrieval by Combining Ranked List and Clustering. Proceedings of RIAO, College de France, pp. 665-681, 2000.
    • (2000) Proceedings of RIAO , pp. 665-681
    • Leuski, A.1    Allan, J.2
  • 12


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.