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Representation Learning for Natural Language Processing - Softcover

 
9789811555749: Representation Learning for Natural Language Processing

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Inhaltsangabe

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.

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Weitere beliebte Ausgaben desselben Titels

9789811555725: Representation Learning for Natural Language Processing

Vorgestellte Ausgabe

ISBN 10:  9811555729 ISBN 13:  9789811555725
Verlag: Springer, 2020
Hardcover