Evaluation of Text Summaries Based on Linear Optim

Rojas-Simon, Jonathan; Ledeneva, Yulia; Garcia-Hernandez, Rene Arnulfo

ISBN 10: 3031072162 / ISBN 13: 9783031072161

Editore: Springer, 2023

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pp. 232. Codice articolo 26398548998

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Titolo: Evaluation of Text Summaries Based on Linear...

Casa editrice: Springer

Data di pubblicazione: 2023

Legatura: Brossura

Condizione: New

Descrizione articolo

Riassunto:

This book provides a comprehensive discussion and new insights about linear optimization of content metrics to improve the automatic Evaluation of Text Summaries (ETS). The reader is first introduced to the background and fundamentals of the ETS. Afterward, state-of-the-art evaluation methods that require or do not require human references are described. Based on how linear optimization has improved other natural language processing tasks, we developed a new methodology based on genetic algorithms that optimize content metrics linearly. Under this optimization, we propose SECO-SEVA as an automatic evaluation metric available for research purposes. Finally, the text finishes with a consideration of directions in which automatic evaluation could be improved in the future. The information provided in this book is self-contained. Therefore, the reader does not require an exhaustive background in this area. Moreover, we consider this book the first one that deals with the ETS in depth.