메뉴 건너뛰기




Volumn , Issue , 2010, Pages 604-607

An improved Non-negative Matrix Factorization algorithm for combining multiple clusterings

Author keywords

Clustering; K Mean; Machine learning; Non negative matrix factorization

Indexed keywords

ADJACENT MATRIX; BASIS MATRIX; CLUSTER ENSEMBLES; CLUSTERING; CLUSTERING RESULTS; COEFFICIENT MATRIX; HOT SPOT; HYPERGRAPH; INDICATOR MATRIX; K-MEAN; K-MEANS ALGORITHM; KEY PROBLEMS; MACHINE LEARNING COMMUNITIES; MACHINE-LEARNING; MATRIX; MULTIPLE CLUSTERINGS; NON-NEGATIVE MATRIX FACTORIZATION ALGORITHMS; NONNEGATIVE MATRIX FACTORIZATION; REAL-WORLD DATASETS;

EID: 77956431446     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MVHI.2010.72     Document Type: Conference Paper
Times cited : (5)

References (11)
  • 2
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles - A knowledge reuse framework for combining partitionings
    • A. Strehl, and J. Ghosh, "Cluster ensembles - a knowledge reuse framework for combining partitionings", Journal of Machine Learning Research, 2002, pp. 583-617.
    • (2002) Journal of Machine Learning Research , pp. 583-617
    • Strehl, A.1    Ghosh, J.2
  • 7
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • D. D. Lee, H. S. Seung, "Learning the parts of objects by non-negative matrix factorization", Nature, 1999, pp. 788-791.
    • (1999) Nature , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 9
    • 0032131147 scopus 로고    scopus 로고
    • A fast and high quality multilevel scheme for partitioning irregular graphs
    • PII S1064827595287997
    • G. Karypis, and V. Kumar, "A fast and high quality multilevel scheme for partitioning irregular graphs", SIAM Journal on Scientific Computing, USA, 1998, pp. 359-392. (Pubitemid 128689516)
    • (1998) SIAM Journal of Scientific Computing , vol.20 , Issue.1 , pp. 359-392
    • Karypis, G.1    Kumar, V.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.