Evaluation Of Text Summaries Based On Linear Optimization Of Content Metrics
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Evaluation of Text Summaries Based on Linear Optimization of Content Metrics
Author: Jonathan Rojas-Simon
language: en
Publisher: Springer Nature
Release Date: 2022-08-18
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.
Explainable AI Within the Digital Transformation and Cyber Physical Systems
Author: Moamar Sayed-Mouchaweh
language: en
Publisher: Springer Nature
Release Date: 2021-10-30
This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
Pattern Recognition
Author: Osslan Osiris Vergara-Villegas
language: en
Publisher: Springer Nature
Release Date: 2022-06-10
This book constitutes the proceedings of the 14th Mexican Conference on Pattern Recognition, MCPR 2022, which was held in planned to be held Ciudad Juárez, Mexico, in June 2022. The 33 papers presented in this volume were carefully reviewed and selected from 66 submissions. They are organized in the following topical sections: pattern recognition techniques; neural networks and deep learning; image and signal processing and analysis; natural language processing and recognition; robotics and remote sensing applications of pattern recognition; medical applications of pattern recognition.