Evaluation of Text Summaries Based on Linear Optimization of Content Metrics

Jonathan Rojas-Simon (u. a.)

ISBN 10: 3031072162 ISBN 13: 9783031072161
Verlag: Springer, 2023
Neu Taschenbuch

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Beschreibung

Beschreibung:

Evaluation of Text Summaries Based on Linear Optimization of Content Metrics | Jonathan Rojas-Simon (u. a.) | Taschenbuch | xv | Englisch | 2023 | Springer | EAN 9783031072161 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Bestandsnummer des Verkäufers 127335970

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Inhaltsangabe:

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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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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Bibliografische Details

Titel: Evaluation of Text Summaries Based on Linear...
Verlag: Springer
Erscheinungsdatum: 2023
Einband: Taschenbuch
Zustand: Neu

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