Statistical approaches to automatic text summarization

Bulletin of the American Society for Information Science and Technology

Volumn 30, Issue 4, 2004, Pages 21-25

  McCargar, Victoria ^a  

^a Los Angeles Times Editorial Library   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 28444446746     PISSN: 19316550     EISSN: 00954403     Source Type: Trade Journal    
DOI: 10.1002/bult.319     Document Type: Review

References (8)

1. Feldman, S. ( 1999, May). NLP meets the jabberwocky: Natural language processing in information retrieval. Online, 23, 62 ‐ 72.
2. The challenges of automatic summarization
3. Hovy, E., & Lin, C. ‐Y. ( 1999). Automated text summarization in Summarist. In I. Mani and M. Maybury (Eds.), Advances in automatic text summarization (pp. 81 ‐ 94). Cambridge, MA: MIT Press.
4. Kupiec, J., Pedersen, J. & Chen, F. ( 1995). A trainable document summarizer. Proceedings of the 18th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 68 ‐ 73). New York: ACM Press.
5. Mueller, E. T. ( 1999). Prospects for in‐depth story understanding by computer. Project Xenia, Media Laboratory, Massachusetts Institute of Technology. Retrieved February 3, 2004, from http://xenia.media.mit.edu/˜mueller/papers/storyund.html.
6. Pinto, M. & Galvez, C. ( 1999). Paradigms for abstracting systems. Journal of Information Science 25, 365 ‐ 380.
7. Salton, G., Singhal, A., Mitra, M., & Buckley, C. ( 1997). Automatic text structuring and summarization. Information Processing and Management 33, 193 ‐ 207.
8. Sparck Jones, K. ( 1999). Automated text summarization in Summarist. In I. Mani and M. Maybury (Eds.), Advances in automatic text summarization (pp. 2 ‐ 12). Cambridge, MA: MIT Press.