Integrating clustering and multi-document summarization to improve document understanding

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2008, Pages 1435-1436

  Wang, Dingding ^a   Zhu, Shenghuo ^b   Li, Tao ^a   Chi, Yun ^b   Gong, Yihong ^b  

^a The Department of Electrical and Computer Engineering   (United States)

^b NEC LABORATORIES AMERICA   (United States)

Author keywords

Document clustering; Multi document summarization; Nonnegative matrix factorization with given bases

Indexed keywords

CLUSTERING METHODS; DOCUMENT CLUSTERING; DOCUMENT CONTEXT; DOCUMENT MATRICES; DOCUMENT SUMMARIZATION; LANGUAGE MODEL; MULTI-DOCUMENT SUMMARIZATION; NONNEGATIVE MATRIX FACTORIZATION WITH GIVEN BASES;

CLUSTER ANALYSIS; COMPUTATIONAL LINGUISTICS; FACTORIZATION; INFORMATION RETRIEVAL; KNOWLEDGE MANAGEMENT; LIGHT MEASUREMENT;

CLUSTERING ALGORITHMS;

EID: 70349254547     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1458082.1458319     Document Type: Conference Paper

References (6)

1. H. Cho, I. Dhillon, Y. Guan, and S. Sra. Minimum sum squared residue co-clustering. In Proceedings of SIAM Data Mining 2004.
2. I. Dhillon, S. Mallela, and S. Modha. Information-theoretic co-clustering. In Proceedings of SIGKDD 2001.
3. C. Ding, T. Li, W. Peng, and H. Park. Orthogonal nonnegative matrix tri-factorizations for clustering. In Proceedings of SIGKDD 2006.
4. T. Hofmann. Probabilistic latent semantic indexing. In Proceedings of SIGIR 1999.
5. D. D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. In Proceedings of NIPS 2001.
6. W. Xu, X. Liu, and Y. Gong. Document clustering based on non-negative matrix factorization. In Proceedings of SIGIR 2003.