Automatic condensation of electronic publications by sentence selection☆
References (10)
Constructing literature abstracts by computer: Techniques and prospects
Information Processing & Management
(1990)- et al.
Information extraction and text summarization using linguistic knowledge acquisition
Information Processing & Management
(1989) The ticc: Parsing interesting text
Problems in automatic abstracting
Communications of the ACM
(1964)- et al.
The application of linguistic processing to automatic abstract generation
Journal of Documentation and Text Management
(1993)
There are more references available in the full text version of this article.
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This paper was prepared while Lisa Rau was on an NSF Visiting Professorship for Women grant (NSF GER-9350134), hosted by the Computer and Information Sciences Department at the University of Pennsylvania.
Copyright © 1995 Published by Elsevier Ltd.