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Machine Reading Comprehension
Algorithms and Practice
Presents, for the first time, detailed treatment of machine reading comprehension (MRC), a key technology within natural language processing (NLP), giving basics, models, and hands-on issues in application
Chenguang Zhu (Author)
9780323901185, Elsevier Science
Paperback / softback, published 26 March 2021
270 pages
22.9 x 15.1 x 1.8 cm, 0.45 kg
Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. This volume gives theoretical treatment to solutions and gives detailed analysis of code, and considers applications in real-world industry. The book includes basic concepts, tasks, datasets, NLP tools, deep learning models and architecture, and insight from hands-on experience. In addition, the title presents the latest advances from the past two years of research. Structured into three sections and eight chapters, this book presents the basis of MRC; MRC models; and hands-on issues in application. This book offers a comprehensive solution for researchers in industry and academia who are looking to understand and deploy machine reading comprehension within natural language processing.
Part I: Foundation1. Introduction to Machine Reading Comprehension2. The Basics of Natural Language Processing3. Deep Learning in Natural Language Processing Part II: Architecture4. Architecture of MRC Models5. Common MRC Models6. Pre-trained Language Model Part III: Application7. Code Analysis of SDNet Model8. Applications and Future of Machine Reading Comprehension AppendixA. Machine Learning BasicsB. Deep Learning Basics
Subject Areas: Artificial intelligence [UYQ]