Evaluation of Text Summaries Based on Linear Optimization of Content Metrics

丛 书 名：Studies in Computational Intelligence

版本说明：1st ed. 2022

作     者：Jonathan Rojas-Simon Yulia Ledeneva Rene Arnulfo Garcia-Hernandez 

I S B N：(纸本) 9783031072130 

出 版 社：Springer International Publishing 

出 版 年：2022年

学科分类：0502[文学-外国语言文学] 05[文学] 050211[文学-外国语言学及应用语言学] 

摘      要：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.