Representation and Inference for Natural Language - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Representation and Inference for Natural Language write by Patrick Blackburn. This book was released on 2005. Representation and Inference for Natural Language available in PDF, EPUB and Kindle. 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.
Representation Learning for Natural Language Processing
Representation Learning for Natural Language Processing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Representation Learning for Natural Language Processing write by Zhiyuan Liu. This book was released on 2020-07-03. Representation Learning for Natural Language Processing available in PDF, EPUB and Kindle. 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.
Natural Language Processing and Knowledge Representation
Natural Language Processing and Knowledge Representation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Natural Language Processing and Knowledge Representation write by Łucja M. Iwańska. This book was released on 2000-06-19. Natural Language Processing and Knowledge Representation available in PDF, EPUB and Kindle. "Traditionally, knowledge representation and reasoning systems have incorporated natural language as interfaces to expert systems or knowledge bases that performed tasks separate from natural language processing. As this book shows, however, the computational nature of representation and inference in natural language makes it the ideal model for all tasks in an intelligent computer system. Natural language processing combines the qualitative characteristics of human knowledge processing with a computer's quantitative advantages, allowing for in-depth, systematic processing of vast amounts of information.
Embeddings in Natural Language Processing
Embeddings in Natural Language Processing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Embeddings in Natural Language Processing write by Mohammad Taher Pilehvar. This book was released on 2020-11-13. Embeddings in Natural Language Processing available in PDF, EPUB and Kindle. 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.
Representation and Inference for Natural Language
Representation and Inference for Natural Language - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Representation and Inference for Natural Language write by Patrick Blackburn. This book was released on 1998. Representation and Inference for Natural Language available in PDF, EPUB and Kindle.
