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Volumn , Issue , 2010, Pages 643-648

A new search method for ranking short text messages using semantic features and cluster coherence

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER SIZES; DOCUMENT MATRICES; MULTIPLE USER; NONNEGATIVE MATRIX FACTORIZATION; RANKING METHODS; SEARCH METHOD; SEARCH RESULTS; SEMANTIC FEATURES; SEMANTIC SIMILARITY; TEXT MESSAGES;

EID: 77955163620     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCCYB.2010.5491333     Document Type: Conference Paper
Times cited : (1)

References (9)
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    • J. Kogan, C. Nicholas, M. Teboulle (Eds)
    • D. Zeimpekis, E. Gallopoulos, "TMG: A MATLAB Toolbox for Generating Term-Document Matrices from Text Collections" in J. Kogan, C. Nicholas, M. Teboulle (Eds), Grouping Multidimensional Data, Springer 2006
    • (2006) Grouping Multidimensional Data, Springer
    • Zeimpekis, D.1    Gallopoulos, E.2
  • 3
    • 35548969471 scopus 로고    scopus 로고
    • Projected gradient methods for non-negative matrix factorization
    • C.-J. Lin. "Projected gradient methods for non-negative matrix factorization." Neural Computation, 19 (2007), 2756-2779
    • (2007) Neural Computation , vol.19 , pp. 2756-2779
    • Lin, C.-J.1
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    • Document clustering based on nonnegative matrix factorization
    • ACM Press
    • W. Xu, X. Liu, and Y. Gong, "Document clustering based on nonnegative matrix factorization." In Proceedings of the 26th annual International ACM SIGIR conference, pages 267-273. ACM Press, 2003. doi: http://doi.acm.org/10.1145/860435.860485.
    • (2003) Proceedings of the 26th Annual International ACM SIGIR Conference , pp. 267-273
    • Xu, W.1    Liu, X.2    Gong, Y.3
  • 8
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    • (2010)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.