Hongyan Jing
ABSTRACT
We present a novel sentence reduction system for automatically removing extraneous phrases from sentences that are extracted from a document for summarization purpose. The system uses multiple sources of knowledge to decide which phrases in an extracted sentence can be removed, including syntactic knowledge, context information, and statistics computed from a corpus which consists of examples written by human professionals. Reduction can significantly improve the conciseness of automatic summaries.
- John Carroll, Guido Minnen, Yvonne Canning, Siobhan Devlin, and John Tait. 1998. Practical simplification of English newspaper text to assist aphasic readers. In Proceedings of AAAI-98 Workshop on Integrating Artificial Intelligence and Assistive Technology, Madison, Wisconsin, July.Google Scholar
- R. Chandrasekar, C. Doran, and B. Srinivas. 1996. Motivations and methods for text simplification. In Proceedings of the 16th International Conference on Computational Linguistics (COLING'96), Copenhagen, Denmark, August. Google ScholarDigital Library
- Simon H. Corston-Oliver and William B. Dolan. 1999. Less is more: Eliminating index terms from subordinate clauses. In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics(ACL'99), pages 349--356, University of Maryland, Maryland, June. Google ScholarDigital Library
- Gregory Grefenstette. 1998. Producing intelligent telegraphic text reduction to provide an audio scanning service for the blind. In Working Notes of AAAI 1998 Spring Symposium on Intelligent Text Summarization, Stanford University, Standford, California, March.Google Scholar
- Hongyan Jing and Kathleen R. McKeown. 1998. Combining multiple, large-scale resources in a reusable lexicon for natural language generation. In Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and the 17th International Conference on Computational Linguistics, volume 1, pages 607--613, Université de Montréal, Quebec, Canada, August. Google ScholarDigital Library
- Hongyan Jing and Kathleen R. McKeown. 1999. The decomposition of human-written summary sentences. In Proceedings of the 22nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 129--136, University of Berkeley, CA, August. Google ScholarDigital Library
- Hongyan Jing and Kathleen R. McKeown. 2000. Cut and paste based text summarization. In Proceedings of NAACL 2000. Google ScholarDigital Library
- Beth Levin. 1993. English Verb Classes and Alternations: A Preliminary Investigation. University of Chicago Press, Chicago, Illinois.Google Scholar
- Catherine Macleod and Ralph Grishman, 1995. COMLEX Syntax Reference Manual. Proteus Project, New York University.Google Scholar
- Michael McCord, 1990. English Slot Grammar. IBM.Google Scholar
- George A. Miller, Richard Beckwith, Christiane Fellbaum, Derek Gross, and Katherine J. Miller. 1990. Introduction to WordNet: An on-line lexical database. International Journal of Lexicography (special issue), 3(4):235--312.Google Scholar
- George A. Miller, Claudia Leacock, Randee Tengi, and Ross T. Bunker. 1993. A semantic concordance. Cognitive Science Laboratory, Princeton University.Google Scholar
- Sentence reduction for automatic text summarization
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