Integración del reconocimiento de la implicación textual en tareas automáticas de resúmenes de textos

1. Lloret Pastor, Elena
2. Ferrández Escámez, Óscar
3. Muñoz Guillena, Rafael
4. Palomar Sanz, Manuel

Export

Export

×

MLA

modern-language-association

APA

apa

Chicago

chicago-fullnote-bibliography

Harvard

harvard-cite-them-right

Vancouver

vancouver-author-date

---

RIS BibTex

Export

×

This document cannot be exported because it belongs to another portal.

Full text

lock_openRUA externo

DIALNET GOOGLE SCHOLAR lock_openRUA editor

More publications in: Procesamiento del lenguaje natural

Abstract

This paper presents a preliminary study of the usefulness of applying textual entailment recognition in text summarization tasks. Two different approaches are proposed. The first one relies on the word's frequency in order to select the most relevant sentences to include in the final summary, whereas the second one combines textual entailment recognition together with the aforementioned approach so that we can reduce the size of the original text or texts first. Results show that this combination has been appropriate, obtaining an increase of 5.85 % for single-document and of 6.80 % for multi-document when textual entailment and the frequency of words are applied together.

Data source: Dialnet