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Selective Analysis for Automatic Abstracting: Evaluating Indicativeness and Acceptability (2000)
| Venue: | Association for Computational |
BibTeX
@INPROCEEDINGS{And00selectiveanalysis,
author = {Horacio Saggion And and Horacio Saggion and Guy Lapalme},
title = {Selective Analysis for Automatic Abstracting: Evaluating Indicativeness and Acceptability},
booktitle = {Association for Computational},
year = {2000}
}
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Abstract
We have developed a new methodology for automatic abstracting of scientific and technical articles called Selective Analysis. This methodology allows the generation of indicativeinformative abstracts integrating different types of information extracted from the source text. The indicative part of the abstract identifies the topics of the document while the informative one elaborates some topics according to the reader's interest. The first evaluation of our methodology demonstrates that Selective Analysis performs well in the task of signaling the topic of the document demonstrating the viability of such a technique. The sentences the system produces from instantiated templates are considered to be as acceptable as human produced sentences. 1 Introduction Automatic abstracting of textual data can be seen as a process composed of four main steps: (i) the source text is interpreted in order to obtain a "meaning" representation of the source; (ii) the representation is then used ...
Keyphrases
selective analysis automatic abstracting evaluating indicativeness source text textual data first evaluation introduction automatic abstracting different type new methodology meaning representation selective analysis performs indicative part technical article indicativeinformative abstract main step
