Abstract
We describe and evaluate SumUM, a text summarization system that produces indicative-informative abstracts for technical papers. Our approach consists of the shallow syntactic and conceptual analysis of the source document and of the implementation of text re-generation techniques based on a study of abstracts produced by professional abstractors. In an evaluation of indicative content in a categorization task, we observed no differences with other automatic method, while differences are observed in an evaluation of informative content. In an evaluation of text quality, the abstracts were considered acceptable when compared with other automatic abstracts. © Springer-Verlag 2000.
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CITATION STYLE
Saggion, H., & Lapalme, G. (2000). Summary generation and evaluation in SumUM. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1952, 329–338. https://doi.org/10.1007/3-540-44399-1_34
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