Automatic abstracting important sentences

International Journal of Information Technology and Decision Making

Volumn 4, Issue 1, 2005, Pages 141-152

  Ren, F J ^a  

^a UNIVERSITY OF TOKUSHIMA   (Japan)

Author keywords

Automatic Extraction of Important Sentence; Statistical information; Structural feature; Web

Indexed keywords

EID: 33746241994     PISSN: 02196220     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219622005001428     Document Type: Article

References (21)

1. I. Sasaki, S. Masuyama and S. Naito, Lexica cohesion based extraction of key sentences, Natural Language Processing 98-9 (1993) 65-71.
2. H. Suzuki, S. Masuyama and S. Naito, Examination of keyword extraction using thesaurus in Japanese text, Natural Language Processing 98-10 (1993) 73-79.
3. K. Kondo, Y. Arai and F. Kozato, A method of summarising used paraphrasing a part of text, Technical Report of IEICE, NLC95-62 (1995) 25-30.
4. T. Funasaka, K. Yamamoto and S. Masuyama, Relevant newspapaer articles summarization by redundancy reduction, Technical Report of IEICE, NLC96-15 (1996) 39-46.
5. J. Kupiec, J. Pedersen and F. Chen, A trainable document summarize, in Proceedings of SIGIR '95 (1995), pp. 68-73.
6. H. P. Luhn, The automatic creation of literature abstrats, IBM Journal of Research and Development 2-2 (1958) 159-165.
7. K. Zechner, Fast generation of abstracts from general domain text corpora by extracting relevant sentences, in Proceedings of 16th COLING (1996), pp. 986-989.
8. J. D. Cohen, Highlights: Language- and domain-independent automatic indexing term for abstracting, Journal of the American Society for Information Science 46(3) (1995) 162-174.
9. M. P. Molina, Documentary abstracting: Toward a methodological model, Journal of the American Society for Information Science 46(3) (1995) 225-234.
10. G. Salton, A. Singhal, M. Mitra and C. Buckley, Automatic text structuring and summarization, Information Processing & Management 33(2) (1997) 193-207.
11. C. D. Paice, Constructing literature abstracts by computer: Techniques and prospects, Information Processing & Management 26(1) (1990) 171-186.
12. A. Goh and S. C. Hui, TES: A text extraction system, Microcomputers for Information Management: Global Internetworking for Libraries 13(1) (1996) 41-56.
13. K. McKeown, J. Robin and K. Kukich, Generating concise natural language summaries, Information Processing & Management 31(5) (1995) 703-733.
14. F. Ren and Y. Sadanaga, An automatic extraction of important sentences using statistical information and structural feature, Natural Language Processing 125(7) (1998) 71-78.
15. D. Marcu, Improving summarization through rhetorical parsing tuning, in Proceedings of the 6th Workshop on Very Large Corpora (1998), pp. 206-215.
16. R. Ochitani, Y. Nakao and F. Nishino, Goal-directed approach for text summarization, in Proceedings of the ACL Workshop on Intelligent Scalable Text Summarization, (1997) 47-50.
17. D. R. Radev and K.R,. McKeown, Generating natural language summaries from multiple on-line sources, Computational Linguistics 24(3) (1998) 469-500.
18. H. Watanabe, A method for abstracting newspaper articles by using surface clues, in Proceedings of the 16th International Conference on Computational Linguistics (1996), pp. 947-979.
19. Y. Matsumoto, S. Kurohashi, Y. Nyoki, H. Shinho and M. Nagao, User's guide for the JUMAN system, a user-extensible morphological analyzer for Japanese (1995).
20. F. Ren and J. Nie, Automatic extraction of important sentences using statistical information and structural features, in Proc. International Conference on Artificial Intelligence and Soft Computing (2000), pp. 479-486.
21. G. Marchionini and H. Maurer, The roles of digital libraries in teaching and learning, Communications of the ACM 38(4) (1995) 67-75.