Saggion, H. and Lapalme, G. (2002) Generating indicative-informative summaries with SumUM. Computational Linguistics, 28 (4). pp. 497-526. ISSN 0891-2017Full text available as:
We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies.
|Copyright, Publisher and Additional Information:||© 2002 Association for Computational Linguistics. Reproduced in accordance with the publisher's self-archiving policy.|
|Institution:||The University of Sheffield|
|Academic Units:||The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)|
|Depositing User:||Repository Officer|
|Date Deposited:||31 Jul 2006|
|Last Modified:||06 Jun 2014 08:30|