Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.

Science 3 June 1994:
Vol. 264. no. 5164, pp. 1421 - 1426
DOI: 10.1126/science.264.5164.1421
Prev | Table of Contents | Next

Articles

Automatic Analysis, Theme Generation, and Summarization of Machine-Readable Texts

Gerard Salton 1, James Allan 1, Chris Buckley 1, and Amit Singhal 1

1 Department of Computer Science, Cornell University, Ithaca, NY 14853-7501, USA.

Vast amounts of text material are now available in machine-readable form for automatic processing. Here, approaches are outlined for manipulating and accessing texts in arbitrary subject areas in accordance with user needs. In particular, methods are given for determining text themes, traversing texts selectively, and extracting summary statements that reflect text content.


THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Computer-Supported Content Analysis: Trends, Tools, and Techniques.
W. Evans (1996)
Social Science Computer Review 14, 269-279
   Abstract »    PDF »
Performance of Text Retrieval Systems.
G. Salton (1995)
Science 268, 1418-1419
   PDF »
Gauging Similarity with n-Grams: Language-Independent Categorization of Text.
M. Damashek (1995)
Science 267, 843-848
   Abstract »    PDF »


To Advertise     Find Products

Science. ISSN 0036-8075 (print), 1095-9203 (online)