The Semantic Representation Of Natural Language

Download or read book The Semantic Representation of Natural Language written by Michael Levison and published by A&C Black. This book was released on 2012-12-20 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains a detailed, precise and clear semantic formalism designed to allow non-programmers such as linguists and literary specialists to represent elements of meaning which they must deal with in their research and teaching. At the same time, by its basis in a functional programming paradigm, it retains sufficient formal precision to support computational implementation. The formalism is designed to represent meaning as found at a variety of levels, including basic semantic units and relations, word meaning, sentence-level phenomena, and text-level meaning. By drawing on fundamental principles of program design, the proposed formalism is both easy to read and modify yet sufficiently powerful to allow for the representation of complex semantic phenomena. In this monograph, the authors introduce the formalism and show its basic structure, apply it to the analysis of the semantics of a variety of linguistic phenomena in both English and French, and use it to represent the semantics of a variety of texts ranging from single sentences, to textual excepts, to a full story.

Download or read book Knowledge Representation and the Semantics of Natural Language written by Hermann Helbig and published by Springer Science & Business Media. This book was released on 2005-12-19 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language is not only the most important means of communication between human beings, it is also used over historical periods for the pres- vation of cultural achievements and their transmission from one generation to the other. During the last few decades, the ?ood of digitalized information has been growing tremendously. This tendency will continue with the globali- tion of information societies and with the growing importance of national and international computer networks. This is one reason why the theoretical und- standing and the automated treatment of communication processes based on natural language have such a decisive social and economic impact. In this c- text, the semantic representation of knowledge originally formulated in natural language plays a central part, because it connects all components of natural language processing systems, be they the automatic understanding of natural language (analysis), the rational reasoning over knowledge bases, or the g- eration of natural language expressions from formal representations. This book presents a method for the semantic representation of natural l- guage expressions (texts, sentences, phrases, etc. ) which can be used as a u- versal knowledge representation paradigm in the human sciences, like lingu- tics, cognitive psychology, or philosophy of language, as well as in com- tational linguistics and in arti?cial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.

Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.

Download or read book Representation and Inference for Natural Language written by Patrick Blackburn and published by Center for the Study of Language and Information Publica Tion. This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.

Download or read book Embeddings in Natural Language Processing written by Mohammad Taher Pilehvar and published by Morgan & Claypool Publishers. This book was released on 2020-11-13 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.

Download or read book Natural Language Processing written by Epaminondas Kapetanios and published by CRC Press. This book was released on 2013-11-14 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the semantic aspects of natural language processing and its applications. Topics covered include: measuring word meaning similarity, multi-lingual querying, and parametric theory, named entity recognition, semantics, query language, and the nature of language. The book also emphasizes the portions of mathematics needed to under

Download or read book Handbook of Research on Natural Language Processing and Smart Service Systems written by Pazos-Rangel, Rodolfo Abraham and published by IGI Global. This book was released on 2020-10-02 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) is a branch of artificial intelligence that has emerged as a prevalent method of practice for a sizeable amount of companies. NLP enables software to understand human language and process complex data that is generated within businesses. In a competitive market, leading organizations are showing an increased interest in implementing this technology to improve user experience and establish smarter decision-making methods. Research on the application of intelligent analytics is crucial for professionals and companies who wish to gain an edge on the opposition. The Handbook of Research on Natural Language Processing and Smart Service Systems is a collection of innovative research on the integration and development of intelligent software tools and their various applications within professional environments. While highlighting topics including discourse analysis, information retrieval, and advanced dialog systems, this book is ideally designed for developers, practitioners, researchers, managers, engineers, academicians, business professionals, scholars, policymakers, and students seeking current research on the improvement of competitive practices through the use of NLP and smart service systems.