You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
This book highlights cutting-edge research relevant to the building of a computational model of reading comprehension, as in the processing and understanding of a natural language text or story. The book takes an interdisciplinary approach to the study of reading, with contributions from computer science, psychology, and philosophy. Contributors cover the theoretical and psychological foundations of the research in discussions of what it means to understand a text, how one builds a computational model, and related issues in knowledge representation and reasoning. The book also addresses some of the broader issues that a natural language system must deal with, such as reading in context, linguistic novelty, and information extraction.
This new Springer volume provides a comprehensive and detailed look at current approaches to automated question answering. The level of presentation is suitable for newcomers to the field as well as for professionals wishing to study this area and/or to build practical QA systems. The book can serve as a "how-to" handbook for IT practitioners and system developers. It can also be used to teach graduate courses in Computer Science, Information Science and related disciplines.
Sentiment analysis research has been started long back and recently it is one of the demanding research topics. Research activities on Sentiment Analysis in natural language texts and other media are gaining ground with full swing. But, till date, no concise set of factors has been yet defined that really affects how writers’ sentiment i.e., broadly human sentiment is expressed, perceived, recognized, processed, and interpreted in natural languages. The existing reported solutions or the available systems are still far from perfect or fail to meet the satisfaction level of the end users. The reasons may be that there are dozens of conceptual rules that govern sentiment and even there are possibly unlimited clues that can convey these concepts from realization to practical implementation. Therefore, the main aim of this book is to provide a feasible research platform to our ambitious researchers towards developing the practical solutions that will be indeed beneficial for our society, business and future researches as well.
This book is the first to present a comprehensive theory of non-canonical questions, those question types that do not (only) request information from the addressee, but rather (additionally) tell us something about the speaker's epistemic and/or emotional state, such as can't-find-the-value questions, echo questions, rhetorical questions, and surprise questions. While much recent research has explored the formal semantics and the phonetics and phonology of both canonical and non-canonical questions, the literature is still lacking a comprehensive account from a syntax-pragmatics perspective that brings together the multiple findings and strands of research from the last twenty years. The sta...
The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the “factual” aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual asse...
Digital Libraries are complex and advanced forms of information systems which extend and augment their physical counterparts by amplifying existing resources and services and enabling development of new kinds of human problem solving and expression. Their complexity arises from the data-rich domain of discourse as well as from extended demands for multi-disciplinary input, involving distributed systems architectures, structured digital documents, collaboration support, human-computer interaction, information filtering, etc. In addition to the broad range of technical issues, ethics and intellectual property rights add to the complication that is normally associated with the development, main...
A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.
Linguistics, Corpus Linguistics, and Machine Translation." --Book Jacket.