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181   $ctxt$2rdacontent
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200 10$aEvaluation of Text Summaries Based on Linear Optimization of Content Metrics /$fby Jonathan Rojas-Simon, Yulia Ledeneva, Rene Arnulfo Garcia-Hernandez
205   $a1st ed. 2022.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022.
215   $a1 online resource (222 pages)
225 1 $aStudies in Computational Intelligence,$x1860-9503 ;$v1048
311 08$aPrint version: Rojas-Simon, Jonathan Evaluation of Text Summaries Based on Linear Optimization of Content Metrics Cham : Springer International Publishing AG,c2022 9783031072130 
327   $aIntroduction -- Background of the ETS -- Fundamentals of the ETS -- State-of-the-art Automatic Evaluation Methods -- A Novel Methodology based on Linear Optimization of Metrics for the ETS -- Experimenting with Linear Optimization of Metrics for Single-document Summarization Evaluation -- Experimenting with Linear Optimization of Metrics for Multi-document Summarization Evaluation -- Conclusions and future considerations for the ETS.
330   $aThis book provides a comprehensive discussion and new insights about linear optimization of content metrics to improve the automatic Evaluation of Text Summaries (ETS). The reader is first introduced to the background and fundamentals of the ETS. Afterward, state-of-the-art evaluation methods that require or do not require human references are described. Based on how linear optimization has improved other natural language processing tasks, we developed a new methodology based on genetic algorithms that optimize content metrics linearly. Under this optimization, we propose SECO-SEVA as an automatic evaluation metric available for research purposes. Finally, the text finishes with a consideration of directions in which automatic evaluation could be improved in the future. The information provided in this book is self-contained. Therefore, the reader does not require an exhaustive background in this area. Moreover, we consider this book the first one that deals with the ETS in depth.
410  0$aStudies in Computational Intelligence,$x1860-9503 ;$v1048
606   $aComputational intelligence
606   $aEngineering$xData processing
606   $aBig data
606   $aComputational Intelligence
606   $aData Engineering
606   $aBig Data
615  0$aComputational intelligence.
615  0$aEngineering$xData processing.
615  0$aBig data.
615 14$aComputational Intelligence.
615 24$aData Engineering.
615 24$aBig Data.
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700   $aRojas-Simon$b Jonathan$01253939
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996   $aEvaluation of Text Summaries Based on Linear Optimization of Content Metrics$92907782
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