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Representation Learning for Natural Language Processing
Hardcover
LinguisticsDatabasesGeneral Computers
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ISBN13: 9789811555725
Publisher: Springer Nature
Published: Jul 4 2020
Pages: 334
Weight: 1.50
Height: 0.81 Width: 6.14 Depth: 9.21
Language: English
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.
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