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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics: 1048 (Studies in Computational Intelligence) - Tapa dura
Sinopsis
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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Acerca del autor
Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.
De la contraportada
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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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics
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Springer International Publishing, 2022
ISBN 10: 3031072138
ISBN 13: 9783031072130
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Librería: Buchpark, Trebbin, Alemania
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Condición: Hervorragend. Zustand: Hervorragend | Seiten: 232 | Sprache: Englisch | Produktart: Bücher. Nº de ref. del artículo: 40093145/1
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Evaluation of Text Summaries based on Linear Optimization of Content Metrics
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ISBN 10: 3031072138
ISBN 13: 9783031072130
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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. Afterwa. Nº de ref. del artículo: 585900091
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics (Studies in Computational Intelligence, 1048)
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics
Impresión bajo demandaLibrería: Revaluation Books, Exeter, Reino Unido
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Hardcover. Condición: Brand New. 228 pages. 9.25x6.10x0.56 inches. In Stock. This item is printed on demand. Nº de ref. del artículo: __3031072138
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics
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Springer International Publishing Aug 2022, 2022
ISBN 10: 3031072138
ISBN 13: 9783031072130
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 232 pp. Englisch. Nº de ref. del artículo: 9783031072130
Cantidad disponible: 2 disponibles
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics
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Springer International Publishing, 2022
ISBN 10: 3031072138
ISBN 13: 9783031072130
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783031072130
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics
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Springer International Publishing, Springer Nature Switzerland Aug 2022, 2022
ISBN 10: 3031072138
ISBN 13: 9783031072130
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Buch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch. Nº de ref. del artículo: 9783031072130
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics (Studies in Computational Intelligence, 1048)
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics (Studies in Computational Intelligence, 1048)
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics
Librería: Revaluation Books, Exeter, Reino Unido
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Hardcover. Condición: Brand New. 228 pages. 9.25x6.10x0.56 inches. In Stock. Nº de ref. del artículo: x-3031072138
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