Evaluation of Text Summaries Based on Linear Optimization of Content Metrics
Buch in deiner Nähe kaufen
Beschreibung
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.
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.
Introduces the reader to the background and fundamentals of the Evaluation of Text Summaries (ETS) Provides state-of-the-art studies and new methodologies for improving the ETS Shows the design of experiments that combine evaluation metrics for the ETS
Autor*in
Jonathan Rojas-Simon
Themen in »Evaluation of Text Summaries Based on Linear Optimization of Content Metrics«
Automatic Text Summarization (ATS) Natural Language Generation Tasks Evaluation of Text Summaries (ETS) Content-Based Metrics Linear Optimization Genetic Algorithm (GA) Intrinsic Evaluation Latent Semantic Analysis (LSA) ROUGE-C Jensen-Shannon Divergence