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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics

Studies in Computational Intelligence 1048
ISBN/EAN: 9783031072130
Umbreit-Nr.: 5545476

Sprache: Englisch
Umfang: xv, 213 S., 46 s/w Illustr., 11 farbige Illustr.,
Format in cm:
Einband: gebundenes Buch

Erschienen am 19.08.2022
Auflage: 1/2022
€ 160,49
(inklusive MwSt.)
Lieferbar innerhalb 1 - 2 Wochen
  • Kurztext
    • 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.

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