A new descriptive clustering algorithm based on nonnegative matrix factorization

2008 IEEE International Conference on Granular Computing, GRC 2008

Volumn , Issue , 2008, Pages 407-412

  Li, Zhao ^a   Peng, Hong ^a   Wu, Xindong ^b,c  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b HEFEI UNIVERSITY OF TECHNOLOGY   (China)

^c University of Vermont ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FACTORIZATION; LIGHT MEASUREMENT;

BASIS VECTORS; DOCUMENT MATRIXES; GRADIENT DESCENTS; NON-NEGATIVE MATRIX FACTORIZATIONS; SOME APPLICATIONS; SPARSE REPRESENTATIONS; SQUARED ERROR OBJECTIVE FUNCTIONS; TEXT CLUSTERING; WEIGHTED ELEMENTS; WORD PROBLEMS;

CLUSTERING ALGORITHMS;

EID: 57949101466     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/GRC.2008.4664752     Document Type: Conference Paper

References (8)

1. Patrik O. Hoyer, Non-negative Matrix Factorization with Sparseness Constraints, Journal of Machine Learning Research 5 (2004) 1457-1469.
2. Douglas Fisher. Knowledge Acquisition via Incremental Conceptual Clustering, Machine Learning 1987, (2):129-172.
3. Wayne Iba and Pat Langley, Unsupervised Learning of Probabilistic Concept Hierarchies, Machine Learning and Its Applications, volume 2049 of Lecture Notes in Computer Science, Springer, 2001, pages 39-70,.
4. Ryszard S. Michalski and Robert E. Stepp, Learning from Observation: Conceptual Clustering, Machine Learning: An Artificial Intelligence Approach. Morgan Kaufmann, 1983.
5. Stanisław Osinski, Jerzy Stefanowski, and Dawid Weiss. Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition, In Proceedings of the International Intelligent Information Processing and Web Mining Conference, 2004, pages 359-368.
6. Dawid Weiss, Descriptive Clustering as a Method for Exploring Text Collections, PhD Thesis, Poznan University of Technology Institute of Computing Science, Poland 2006.
7. D. Lee and H. Seung, Algorithms for Non-Negative Matrix Factorization, Advances in Neural Information Processing Systems 2001, 13, 556-562.
8. P. Paatero and U. Tapper, Positive Matrix Factorization: A Non-negative Factor Model with Optimal Utilization of Error Estimates of Data Values. Environmetrics 1994, 5, 111-126.