Representation Learning for Natural Language Processing

This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre—trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre—training techniques. Part II then introduces the related representation techniques to NLP, including gr...