A novel regularized concept factorization for document clustering

[1]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[2]  S. Palmer Hierarchical structure in perceptual representation , 1977, Cognitive Psychology.

[3]  H. Sebastian Seung,et al.  Learning the parts of objects by non-negative matrix factorization , 1999, Nature.

[4]  H. Sebastian Seung,et al.  Algorithms for Non-negative Matrix Factorization , 2000, NIPS.

[5]  Bernhard Schölkopf,et al.  Learning with Local and Global Consistency , 2003, NIPS.

[6]  Xin Liu,et al.  Document clustering based on non-negative matrix factorization , 2003, SIGIR.

[7]  Yihong Gong,et al.  Document clustering by concept factorization , 2004, SIGIR '04.

[8]  Alexander Zien,et al.  Semi-Supervised Learning , 2006 .

[9]  Thomas S. Huang,et al.  Graph Regularized Nonnegative Matrix Factorization for Data Representation. , 2011, IEEE transactions on pattern analysis and machine intelligence.

[10]  Xiaofei He,et al.  Discriminative concept factorization for data representation , 2011, Neurocomputing.

[11]  Jiawei Han,et al.  Locally Consistent Concept Factorization for Document Clustering , 2011, IEEE Transactions on Knowledge and Data Engineering.

[12]  Zhiwu Lu,et al.  Exhaustive and Efficient Constraint Propagation: A Graph-Based Learning Approach and Its Applications , 2011, International Journal of Computer Vision.

[13]  Zhiwu Lu,et al.  Local similarity learning for pairwise constraint propagation , 2013, Multimedia Tools and Applications.

[14]  Xuelong Li,et al.  Local Coordinate Concept Factorization for Image Representation , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[15]  Zhaohui Wu,et al.  Constrained Concept Factorization for Image Representation , 2014, IEEE Transactions on Cybernetics.

[16]  Jun Ye,et al.  Dual-graph regularized concept factorization for clustering , 2014, Neurocomputing.

[17]  Tao Wu,et al.  Automated Graph Regularized Projective Nonnegative Matrix Factorization for Document Clustering , 2014, IEEE Transactions on Cybernetics.

[18]  Sukree Sinthupinyo,et al.  Semi-supervised cluster-and-label with feature based re-clustering to reduce noise in Thai document images , 2015, Knowl. Based Syst..

[19]  Chunxia Zhao,et al.  Local regularization concept factorization and its semi-supervised extension for image representation , 2015, Neurocomputing.

[20]  Xijin Tang,et al.  TESC: An approach to TExt classification using Semi-supervised Clustering , 2015, Knowl. Based Syst..

[21]  Jane You,et al.  Low-rank matrix factorization with multiple Hypergraph regularizer , 2015, Pattern Recognit..

[22]  Vadlamani Ravi,et al.  A survey of the applications of text mining in financial domain , 2016, Knowl. Based Syst..

[23]  Li Zhang,et al.  Constrained neighborhood preserving concept factorization for data representation , 2016, Knowl. Based Syst..

[24]  Yu Zhang,et al.  A Fast Non-Smooth Nonnegative Matrix Factorization for Learning Sparse Representation , 2016, IEEE Access.

[25]  Chunxia Zhang,et al.  Graph-based discriminative concept factorization for data representation , 2017, Knowl. Based Syst..

[26]  Xue Li,et al.  Graph regularized multilayer concept factorization for data representation , 2017, Neurocomputing.