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Representation Learning for Natural Language Processing
Paperback
LinguisticsDatabasesGeneral Computers
ISBN13: 9789811555756
Publisher: Springer Nature
Published: Sep 18 2020
Pages: 334
Weight: 1.11
Height: 0.75 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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