Representation Learning for Natural Language Processing Book Reviews

AUTHOR
Zhiyuan Liu, Yankai Lin & Maosong Sun
SCORE
0
TOTAL RATINGS
104

Representation Learning for Natural Language Processing by Zhiyuan Liu, Yankai Lin & Maosong Sun Book Summary

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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Book Name Representation Learning for Natural Language Processing
Genre Computers
Published
Language English
E-Book Size 20.17 MB

Representation Learning for Natural Language Processing (Zhiyuan Liu, Yankai Lin & Maosong Sun) Book Reviews 2024

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Summary of Representation Learning for Natural Language Processing by Zhiyuan Liu, Yankai Lin & Maosong Sun

The Representation Learning for Natural Language Processing book written by Zhiyuan Liu, Yankai Lin & Maosong Sun was published on 03 July 2020, Friday in the Computers category. A total of 104 readers of the book gave the book 0 points out of 5.

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