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Volumn , Issue , 2011, Pages 774-783

Nonnegative Matrix Tri-Factorization based high-order co-clustering and its fast implementation

Author keywords

Cluster indicator matrix; High order co clustering; Multi type relational data; Nonnegative Matrix Tri Factorization

Indexed keywords

CLUSTERING METHODS; CLUSTERING TECHNIQUES; CO-CLUSTERING; COMPUTATIONALLY EFFICIENT; EXPERIMENTAL EVALUATION; FAST IMPLEMENTATION; HIGH-ORDER; INDICATOR MATRIX; LARGE SIZES; MATRIX MULTIPLICATION; MODERN TECHNOLOGIES; MULTI-TYPE RELATIONAL DATA; NON-NEGATIVE MATRIX; OPTIMIZATION PROBLEMS; REAL WORLD DATA; SOLUTION ALGORITHMS; SUB-PROBLEMS; TRADITIONAL CLUSTERING;

EID: 84863172696     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2011.109     Document Type: Conference Paper
Times cited : (54)

References (23)
  • 1
    • 33749235905 scopus 로고    scopus 로고
    • Spectral clustering for multi-type relational data
    • B. Long, Z. Zhang, X. Wu, and Y. Pu, "Spectral clustering for multi-type relational data," in ICML, 2006.
    • (2006) ICML
    • Long, B.1    Zhang, Z.2    Wu, X.3    Pu, Y.4
  • 2
    • 83055181835 scopus 로고    scopus 로고
    • Simultaneous clustering of multi-type relational data via symmetric nonnegative matrix tri-factorization
    • H. Wang, H. Huang, and D. Hu, "Simultaneous Clustering of Multi-Type Relational Data via Symmetric Nonnegative Matrix Tri-factorization," in CIKM, 2011.
    • (2011) CIKM
    • Wang, H.1    Huang, H.2    Hu, D.3
  • 3
    • 33749575326 scopus 로고    scopus 로고
    • Orthogonal nonnegative matrix t-factorizations for clustering
    • C. Ding, T. Li, W. Peng, and H. Park, "Orthogonal nonnegative matrix t-factorizations for clustering," in SIGKDD, 2006.
    • (2006) SIGKDD
    • Ding, C.1    Li, T.2    Peng, W.3    Park, H.4
  • 4
    • 80051550974 scopus 로고    scopus 로고
    • Graph regularized nonnegative matrix factorization for data representation
    • D. Cai, X. He, J. Han, and T. Huang, "Graph regularized nonnegative matrix factorization for data representation," IEEE TPAMI, 2010.
    • (2010) IEEE TPAMI
    • Cai, D.1    He, X.2    Han, J.3    Huang, T.4
  • 5
    • 70350697580 scopus 로고    scopus 로고
    • Co-clustering on manifolds
    • Q. Gu and J. Zhou, "Co-clustering on manifolds," in SIGKDD, 2009.
    • (2009) SIGKDD
    • Gu, Q.1    Zhou, J.2
  • 6
    • 84880919155 scopus 로고    scopus 로고
    • Fast nonnegative matrix tri-factorization for large-scale data co- clustering
    • H. Wang, F. Nie, H. Huang, and F. Makedon, "Fast Nonnegative Matrix Tri-Factorization for Large-Scale Data Co- Clustering," in IJCAI, 2011.
    • (2011) IJCAI
    • Wang, H.1    Nie, F.2    Huang, H.3    Makedon, F.4
  • 7
    • 0035789644 scopus 로고    scopus 로고
    • Co-clustering documents and words using bipartite spectral graph partitioning
    • I. Dhillon, "Co-clustering documents and words using bipartite spectral graph partitioning," in SIGKDD, 2001.
    • (2001) SIGKDD
    • Dhillon, I.1
  • 8
    • 12244261221 scopus 로고    scopus 로고
    • A generalized maximum entropy approach to bregman coclustering and matrix approximation
    • A. Banerjee, I. Dhillon, J. Ghosh, S. Merugu, and D. Modha, "A generalized maximum entropy approach to bregman coclustering and matrix approximation," in SIGKDD, 2004.
    • (2004) SIGKDD
    • Banerjee, A.1    Dhillon, I.2    Ghosh, J.3    Merugu, S.4    Modha, D.5
  • 9
    • 79956293107 scopus 로고    scopus 로고
    • Orthogonal nonnegative matrix tri-factorization for semi-supervised document co-clustering
    • H. Ma, W. Zhao, Q. Tan, and Z. Shi, "Orthogonal Nonnegative Matrix Tri-factorization for Semi-supervised Document Co-clustering," Advances in Knowledge Discovery and Data Mining, vol. 6119, pp. 189-200, 2010.
    • (2010) Advances in Knowledge Discovery and Data Mining , vol.6119 , pp. 189-200
    • Ma, H.1    Zhao, W.2    Tan, Q.3    Shi, Z.4
  • 10
    • 33749255098 scopus 로고    scopus 로고
    • On the equivalence of nonnegative matrix factorization and spectral clustering
    • C. Ding, X. He, and H. Simon, "On the equivalence of nonnegative matrix factorization and spectral clustering," in SDM, 2005.
    • (2005) SDM
    • Ding, C.1    He, X.2    Simon, H.3
  • 11
    • 84898964201 scopus 로고    scopus 로고
    • Algorithms for non-negative matrix factorization
    • D. Lee and H. Seung, "Algorithms for Non-negative Matrix Factorization," in NIPS, 2001.
    • (2001) NIPS
    • Lee, D.1    Seung, H.2
  • 12
    • 70350679216 scopus 로고    scopus 로고
    • Convex and semi-nonnegative matrix factorizations
    • C. Ding, T. Li, and M. Jordan, "Convex and semi-nonnegative matrix factorizations," IEEE TPAMI, 2010.
    • (2010) IEEE TPAMI
    • Ding, C.1    Li, T.2    Jordan, M.3
  • 13
    • 80052124118 scopus 로고    scopus 로고
    • Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization
    • H. Wang, H. Huang, F. Nie, and C. Ding, "Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization," in SIGIR, 2011.
    • (2011) SIGIR
    • Wang, H.1    Huang, H.2    Nie, F.3    Ding, C.4
  • 14
    • 33750295871 scopus 로고    scopus 로고
    • Latent semantic analysis for multiple-type interrelated data objects
    • X. Wang, J. Sun, Z. Chen, and C. Zhai, "Latent semantic analysis for multiple-type interrelated data objects," in SIGIR, 2006.
    • (2006) SIGIR
    • Wang, X.1    Sun, J.2    Chen, Z.3    Zhai, C.4
  • 15
    • 36849020504 scopus 로고    scopus 로고
    • A probabilistic framework for relational clustering
    • B. Long, Z. Zhang, and P. Yu, "A probabilistic framework for relational clustering," in SIGKDD, 2007.
    • (2007) SIGKDD
    • Long, B.1    Zhang, Z.2    Yu, P.3
  • 16
    • 53849111925 scopus 로고    scopus 로고
    • Semi-supervised clustering via matrix factorization
    • F. Wang, T. Li, and C. Zhang, "Semi-supervised clustering via matrix factorization," in SDM, 2008.
    • (2008) SDM
    • Wang, F.1    Li, T.2    Zhang, C.3
  • 17
    • 77956014774 scopus 로고    scopus 로고
    • Non-negative matrix factorization for semi-supervised heterogeneous data co-clustering
    • Y. Chen, L.Wang, and M. Dong, "Non-negative matrix factorization for semi-supervised heterogeneous data co-clustering," IEEE TKDE, vol. 22, no. 10, pp. 1459-1474, 2010.
    • (2010) IEEE TKDE , vol.22 , Issue.10 , pp. 1459-1474
    • Chen, Y.1    Wang, L.2    Dong, M.3
  • 18
    • 0034244751 scopus 로고    scopus 로고
    • Normalized cuts and image segmentation
    • J. Shi and J. Malik, "Normalized cuts and image segmentation," IEEE TPAMI, vol. 22, no. 8, pp. 888-905, 2000.
    • (2000) IEEE TPAMI , vol.22 , Issue.8 , pp. 888-905
    • Shi, J.1    Malik, J.2
  • 19
    • 49749129595 scopus 로고    scopus 로고
    • Solving consensus and semisupervised clustering problems using nonnegative matrix factorization
    • T. Li, C. Ding, and M. Jordan, "Solving consensus and semisupervised clustering problems using nonnegative matrix factorization," in ICDM, 2007.
    • (2007) ICDM
    • Li, T.1    Ding, C.2    Jordan, M.3
  • 20
    • 77956207894 scopus 로고    scopus 로고
    • Semi-supervised sparse metric learning using alternating linearization optimization
    • W. Liu, S. Ma, D. Tao, J. Liu, and P. Liu, "Semi-supervised sparse metric learning using alternating linearization optimization," in SIGKDD, 2010.
    • (2010) SIGKDD
    • Liu, W.1    Ma, S.2    Tao, D.3    Liu, J.4    Liu, P.5
  • 21
  • 22
    • 0042377235 scopus 로고    scopus 로고
    • Constrained k-means clustering with background knowledge
    • K. Wagstaff, C. Cardie, S. Rogers, and S. Schrödl, "Constrained k-means clustering with background knowledge," in ICML, 2001.
    • (2001) ICML
    • Wagstaff, K.1    Cardie, C.2    Rogers, S.3    Schrödl, S.4
  • 23
    • 42749101928 scopus 로고    scopus 로고
    • Reply networks on a bulletin board system
    • Z. Kou and C. Zhang, "Reply networks on a bulletin board system," Physical Review E, vol. 67, no. 3, p. 36117, 2003.
    • (2003) Physical Review e , vol.67 , Issue.3 , pp. 36117
    • Kou, Z.1    Zhang, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.