Author:
LLORET ELENA,PALOMAR MANUEL
Abstract
AbstractIn this paper, we present a Text Summarisation tool,compendium, capable of generating the most common types of summaries. Regarding the input, single- and multi-document summaries can be produced; as the output, the summaries can be extractive or abstractive-oriented; and finally, concerning their purpose, the summaries can be generic, query-focused, or sentiment-based. The proposed architecture forcompendiumis divided in various stages, making a distinction between core and additional stages. The former constitute the backbone of the tool and are common for the generation of any type of summary, whereas the latter are used for enhancing the capabilities of the tool. The main contributions ofcompendiumwith respect to the state-of-the-art summarisation systems are that (i) it specifically deals with the problem of redundancy, by means of textual entailment; (ii) it combines statistical and cognitive-based techniques for determining relevant content; and (iii) it proposes an abstractive-oriented approach for facing the challenge of abstractive summarisation. The evaluation performed in different domains and textual genres, comprising traditional texts, as well as texts extracted from the Web 2.0, shows thatcompendiumis very competitive and appropriate to be used as a tool for generating summaries.
Publisher
Cambridge University Press (CUP)
Subject
Artificial Intelligence,Linguistics and Language,Language and Linguistics,Software
Cited by
13 articles.
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