A progressive sentence selection strategy for document summarization

Information Processing and Management

Volumn 49, Issue 1, 2013, Pages 213-221

  Ouyang, You ^a   Li, Wenjie ^a   Zhang, Renxian ^a   Li, Sujian ^b   Lu, Qin ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b Peking University   (China)

Author keywords

Asymmetric sentence relationship; Document summarization; Progressive sentence selection; Saliency and coverage

Indexed keywords

ASYMMETRIC SENTENCE RELATIONSHIP; DATA SETS; DOCUMENT SUMMARIZATION; EXPERIMENTAL STUDIES; RANKING METHODS; SALIENCY AND COVERAGE; SALIENCY MEASURE; SENTENCE SELECTION;

MEDIA STREAMING;

DATA PROCESSING;

EID: 84870302829     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2012.05.002     Document Type: Article

References (15)

1. Banerjee, S. & Pedersen, T. (2002). An adapted lesk algorithm for word sense disambiguation using wordnet. In Proceedings of the third international conference on computational linguistics and intelligent text processing (CICLING-02) (pp. 136-145).
2. Carbonell, Jaime G. and Goldstein, Jade. (1998). The use of MMR, diversity-based reranking for reordering documents and producing summaries. In Proceedings of the 21st annual international ACM SIGIR conference on research and development in information retrieval (pp. 335-336). Melbourne, Australia.
3. Conroy, J. M.; Schlesinger, J. D.; & O'Leary, D. P. (2006). Topic-focused multi-document summarization using an approximate oracle score. In Proceedings of the COLING/ACL 2006 main conference poster sessions (pp. 152-159).
4. Cunningham, H.; Maynard, D.; Bontcheva, K. & Tablan, V. (2002). GATE: A framework and graphical development environment for robust NLP tools and applications. In Proceedings of the 40th anniversary meeting of the association for, computational linguistics (pp. 168-175).
5. Katragadda, Rahul & Varma, Vasudeva. (2009). Query-focused summaries or query-biased summaries? In Proceedings of the ACL-IJCNLP 2009 conference short papers (pp. 105-108). Singapore.
6. Kummamuru, K.; Lotlikar, R.; Roy, S.; Singal, K.; & Krishnapuram, R. (2004). A hierarchical monothetic document clustering algorithm for summarization and browsing search results. In Proceedings of WWW 2004 (pp. 658-665). (Pubitemid 40752800)
7. Kupiec, J. M.; Pedersen, J. & Chen, F. (1995) A trainable document summarizer. In Edward A. Fox, Peter Ingwersen, and Raya Fidel, editors, Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in, Information Retrieval, pp. 68-73.
8. Lin, C.Y.; & Hovy, E.H. (2003). Automatic evaluation of summaries using n-gram co-occurrence statistics. In Proceedings of HLT-NAACL2003 (pp. 71-78).
9. Luhn, H. P. (1958). The automatic creation of literature abstracts. IBM Journal of Research and Development, 2(2).
10. Radev, D. R.; Jing, H. & Budzikowska, M. (2000). Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies. In Proceedings of ANLP/NAACL-2000 workshop on summarization (pp. 21-29).
11. Sanderson, M. & Croft, W.B. (1999). Deriving concept hierarchies from text. In Proceedings of SIGIR 1999 (pp. 206-213).
12. Toutanova, K, et al. (2007). The PYTHY summarization system: Microsoft research at DUC 2007. In Document understanding conference 2007. < http://www.duc.nist.gov >.
13. Wan, X.; Yang, J.; & Xiao, J. (2007). Towards iterative reinforcement approach for simultaneous document summarization and keyword extraction. In Proceedings of ACL 2007 (pp. 552-559).
14. Yih, W.; Goodman, J.; Vanderwende, L.; Suzuki, H. (2007). Multi-document summarization by maximizing informative content-words. In Proceedings of IJCAI 2007 (pp. 1776-1782).
15. Zha, Hongyuan (2002). Generic summarization and key phrase extraction using mutual reinforcement principal and sentence clustering. In Proceedings of ACM SIGIR (pp. 113-120).