Multi-document summarization based on BE-vector clustering

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3878 LNCS, Issue , 2006, Pages 470-479

  Liu, Dexi ^a,b   He, Yanxiang ^a   Ji, Donghong ^a,c   Yang, Hua ^a  

^a WUHAN UNIVERSITY   (China)

^b HUBEI UNIVERSITY OF ARTS AND SCIENCE   (China)

^c INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; COMPUTATIONAL LINGUISTICS; COMPUTER SCIENCE; INFORMATION ANALYSIS; SEMANTICS; STRATEGIC PLANNING; TEXT PROCESSING; VECTORS;

BASIC ELEMENT (BE); BE-VECTOR CLUSTERING; K-MEANS CLUSTERING METHOD; MULTI-DOCUMENT SUMMARIZATION;

INFORMATION RETRIEVAL;

EID: 33745582082     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11671299_49     Document Type: Conference Paper

References (14)

1. Radev Dragomir, Jing Hongyan, Budzikowska Malgorzata: Centroid-Based Summarization of Multiple Documents: Sentence Extraction, Utility-Based Evaluation and User Studies. Information Processing and Management, Vol. 40. (2004) 919-938
2. Hardy Hilda: Cross-Document Summarization by Concept Classification. In Proceedings of the 25th annual international ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM Press (2002) 121-128
3. Mitra M., Singhal Amit, Buckley Chris: Automatic Text Summarization by Paragraph Extraction. In ACL/EACL-97 Workshop on Intelligent Scalable Text Summarization, Madrid, Spain (1997) 31-36
4. Knight Kevin, Marcu Daniel: Summarization Beyond Sentence Extraction: a Probabilistic Approach to Sentence Compression. Artificial Intelligence, Vol. 139. (2002) 91-107
5. Barzilay Regina, McKeown Kathleen R., Michael Elhadad: Information Fusion in the Context of Multi-Document Summarization. In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, New Jersey: Association for Computational Linguistics (1999) 550-557
6. Manuel J, MANTA-LO'PEZ: Multi-document Summarization: An Added Value to Clustering in Interactive Retrieval, New York: ACM Transactions on Information Systems, Vol. 22. (2004) 215-241
7. Po Hu, Tingling He, Donghong Ji, Meng Wang: A Study of Chinese Text Summarization Using Adaptive Clustering of Paragraphs. In Proceeding of the Fourth International Conference on Computer and Information Technology (CIT'04), Wuhan, (2004) 1159-1164.
8. Eduard Hovy, Chin-Yew Lin, Liang Zhou, Junichi Fukumoto: Basic Elements. Technical Report, http://www.isi.edurcyl/BE/index.html (2005)
9. Dekang Lin: Minipar. http://www.cs.ualberta.cariindek/minipar.htm (1998)
10. Baeza Yates R., Ribeiro Neto B.: Modern Information Retrieval. New York: Addison Wesley (1999) 27-30
11. Patrick Pantel, Dekang Lin: Document Clustering with Committees. In Proceedings of ACM, SIGIR'02, New York: ACM (2002) 199-206
12. Addrew R. Webb: Statistical Pattern Recognition, 2nd edn. John Wiley & Sons (2002) 376-379
13. Over Paul, Yen James: An Introduction to DUC-2004. In Proceedings of the 4th Document Understanding Conference (DUC 2004) (2004)
14. Chin-Yew Lin, Eduard Hovy: Automatic Evaluation of Summaries Using N-gram Cooccurrence Statistics. In Proceedings of the Human Technology Conference (HLTNAACL-2003), Edmonton, Canada (2003)