A Trainable Document Summarizer.
Julian Kupiec, Jan O. Pedersen, Francine Chen:
A Trainable Document Summarizer.
SIGIR 1995: 68-73@inproceedings{DBLP:conf/sigir/KupiecPC95,
author = {Julian Kupiec and
Jan O. Pedersen and
Francine Chen},
editor = {Edward A. Fox and
Peter Ingwersen and
Raya Fidel},
title = {A Trainable Document Summarizer},
booktitle = {SIGIR'95, Proceedings of the 18th Annual International ACM SIGIR
Conference on Research and Development in Information Retrieval.
Seattle, Washington, USA, July 9-13, 1995 (Special Issue of
the SIGIR Forum)},
publisher = {ACM Press},
year = {1995},
isbn = {0-89791-714-6},
pages = {68-73},
ee = {db/conf/sigir/KupiecPC95.html},
crossref = {DBLP:conf/sigir/95},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
- To summarize is to reduce in complexity, and hence in length, while retaining some of the essential qualities of the original.
- This paper focusses on document extracts, a particular kind of computed document summary.
- Document extracts consisting of roughly 20% of the original can be as informative as the full text of a document, which suggests that even shorter extracts may be useful indicative summmies.
- The trends in our results are in agreement with those of Edmundson who used a subjectively weighted combination of features as opposed to training the feature weights using a corpus.
- We have developed a trainable summarization program that is grounded in a sound statistical framework.
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BibTeX
Printed Edition
Edward A. Fox, Peter Ingwersen, Raya Fidel (Eds.):
SIGIR'95, Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Seattle, Washington, USA, July 9-13, 1995 (Special Issue of the SIGIR Forum).
ACM Press 1995, ISBN 0-89791-714-6
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