Machine Reading Comprehension
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| Author | : Chenguang Zhu |
| Publisher | : Elsevier |
| Total Pages | : 272 |
| Release | : 2021-03-20 |
| Genre | : Computers |
| ISBN | : 0323901190 |
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. Presents the first comprehensive resource on machine reading comprehension (MRC) Performs a deep-dive into MRC, from fundamentals to latest developments Offers the latest thinking and research in the field of MRC, including the BERT model Provides theoretical discussion, code analysis, and real-world applications of MRC Gives insight from research which has led to surpassing human parity in MRC
| Author | : Diego Oliva |
| Publisher | : Springer Nature |
| Total Pages | : 765 |
| Release | : |
| Genre | : Computational intelligence |
| ISBN | : 3030705420 |
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.
| Author | : Johannes Welbl |
| Publisher | : |
| Total Pages | : |
| Release | : 2020 |
| Genre | : |
| ISBN | : |
| Author | : Dan Gutman |
| Publisher | : Simon and Schuster |
| Total Pages | : 168 |
| Release | : 2009-10-27 |
| Genre | : Juvenile Fiction |
| ISBN | : 1442407093 |
Doing homework becomes a thing of the past! Meet the D Squad, a foursome of fifth graders at the Grand Canyon School made up of a geek, a class clown, a teacher's pet, and a slacker. They are bound together by one very big secret: the homework machine. Because the machine, code-named Belch, is doing their homework for them, they start spending a lot of time together, attracting a lot of attention. And attention is exactly what you don't want when you are keeping a secret. Before long, things start to get out of control, and Belch becomes much more powerful than they ever imagined. Now the kids are in a race against their own creation, and the loser could end up in jail...or worse!
| Author | : Sheng Li |
| Publisher | : Springer Nature |
| Total Pages | : 488 |
| Release | : 2021-08-07 |
| Genre | : Computers |
| ISBN | : 3030841863 |
This book constitutes the proceedings of the 20th China National Conference on Computational Linguistics, CCL 2021, held in Hohhot, China, in August 2021. The 31 full presented in this volume were carefully reviewed and selected from 90 submissions. The conference papers covers the following topics such as Machine Translation and Multilingual Information Processing, Minority Language Information Processing, Social Computing and Sentiment Analysis, Text Generation and Summarization, Information Retrieval, Dialogue and Question Answering, Linguistics and Cognitive Science, Language Resource and Evaluation, Knowledge Graph and Information Extraction, and NLP Applications.
| Author | : Kai Sun |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2021 |
| Genre | : |
| ISBN | : |
Machine reading comprehension (MRC) tasks have attracted substantial attention from both academia and industry. These tasks require a machine reader to answer questions relevant to a given document provided as input. In this dissertation, we mainly focus on non-extractive MRC, in which a significant percentage of candidate answers are not restricted to text spans from the reference document or corpus. In comparison to extractive MRC tasks, non-extractive MRC tasks contain a significant percentage of questions focusing on the implicitly expressed facts, events, opinions, or emotions in the given text, requiring diverse types of world knowledge (e.g., commonsense, paraphrase, and arithmetic knowledge) and advanced reading skills (e.g., logical reasoning, summarization, and sentiment analysis). This dissertation presents our work in exploring new challenges and approaches for non-extractive MRC. Specifically, on the challenge side, we create the first MRC dataset that focuses on in-depth multi-turn multi-party dialogue understanding and the first free-form multiple-choice Chinese MRC dataset that requires various kinds of prior knowledge. On the approach side, we propose three general reading strategies and a method of utilizing contextualized knowledge to improve non-extractive MRC. We find our datasets to be very challenging for reading comprehension systems and our approaches to be empirically effective on representative non-extractive MRC tasks.
| Author | : Lu Wang |
| Publisher | : Springer Nature |
| Total Pages | : 861 |
| Release | : 2021-10-11 |
| Genre | : Computers |
| ISBN | : 3030884805 |
This two-volume set of LNAI 13028 and LNAI 13029 constitutes the refereed proceedings of the 10th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2021, held in Qingdao, China, in October 2021. The 66 full papers, 23 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 446 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability.
| Author | : I. Jeena Jacob |
| Publisher | : Springer Nature |
| Total Pages | : 916 |
| Release | : 2021-01-08 |
| Genre | : Technology & Engineering |
| ISBN | : 981158530X |
This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2020), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during 8–9 July 2020. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.
| Author | : Igor V. Tetko |
| Publisher | : Springer Nature |
| Total Pages | : 761 |
| Release | : 2019-09-09 |
| Genre | : Computers |
| ISBN | : 3030304906 |
The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
| Author | : Zongheng Wu |
| Publisher | : |
| Total Pages | : 51 |
| Release | : 2019 |
| Genre | : Artificial intelligence |
| ISBN | : |
