An improved web information summarization based on SSSC

CAR 2010 - 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics

Volumn 3, Issue , 2010, Pages 235-238

  Tang, Jun ^a   Zhao, Xiaojuan ^a  

^a HUNAN URBAN CONSTRUCTION COLLEGE   (China)

Author keywords

Sentence similarity; Soft clustering; Summarization; Web

Indexed keywords

CLUSTER ALGORITHMS; FEATURE FUSION; MULTI-DOCUMENT; NEWS SUMMARIZATION; NUMBER OF CLUSTERS; RELEVANT DOCUMENTS; SENTENCE SIMILARITY; SOFT CLUSTERING; WEB INFORMATION;

FEATURE EXTRACTION; INFORMATION SCIENCE; ROBOTICS; SEARCH ENGINES; TEXT PROCESSING;

CLUSTERING ALGORITHMS;

EID: 77953060015     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CAR.2010.5456674     Document Type: Conference Paper

References (12)

1. Chien-I Lee,Hsiu-Min Chuang. An effective soft clustering approach to mining gene expressions from multi-source databases. Proceedings of the 6th Conference on 6th WSEAS Int. Conf. on Artificial Intelligence, Knowledge Engineering and Data Bases.2007: Pages 165-169.
2. King-Ip Lin, Ravikumar Kondadadi. A Similarity-Based Soft Clustering Algorithm For Documents. 7th International Conference on Database Systems for Advanced Applications (DASFAA '01). 2001.
3. Ani Nenkova, Lucy Vanderwende et al. A compositional context sensitive multi-document summarizer: exploring the factors that influence summarization. Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, 2006. pp: 573-580. (Pubitemid 44626653)
4. Dexi Liu,Yanxiang He,Donghong Ji et al. Multi-document Summarization Based on BE-Vector Clustering. Computational Linguistics and Intelligent Text Processing.2006.
5. Ramiz M. Aliguliyev. A Novel Partitioning-Based Clustering Method and Generic Document Summarization.Web Intelligence and Intelligent Agent Technology Workshops. Dec. 2006 Page(s):626-629.
6. Qin Bing, Liu Ting, Zhang Yu, Li Sheng. Research on Multi-Document Summarization Based on Latent Semantic Indexing. Journal of Harbin Institute of Technology, 2005, 12(1): 91-94. (Pubitemid 40600935)
7. Dragomir R.Radev et al. Centroid-based summarization of multiple documents. Information Processing and Management: an International Journal, Vol. 40, pp. 919-938, 2004.
8. Metzler, D., Bernstein, Y., Croft, W.B., Moffat, A. and Zobel, J., Similarity Measures for Tracking Information Flow. in the Proceedings of the ACM Fourteenth Conference on Information and Knowledge Management (CIKM 2005). pp. 517-524. 2005.
9. James Allan, A. Bolivar, and C. Wade. Retrieval and novelty detection at the sentence level. In Proc. 26th Ann. International ACM SIGIR Conf. on Research and Development in Information Retrieval, pages 314-321, 2003.
10. J. Carbonell and J. Goldstein.1998. The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries. In Proceedings of SIGIR'98. Melbourne, Australia, 1998.
11. Hoa Trang Dang. 2005. Overview of DUC 2005. In Proceedings of DUC2005.
12. C.-Y. Lin and E.H. Hovy. Automatic Evaluation of Summaries Using N-gram Co-occurrence Statistics. In Proceedings of HLT-NA ACL 2003