Representation Learning for Natural Language Processing
Representation Learning for Natural Language Processing
English | 2023 | ISBN: 9819915996, 981991602X | 521 Pages | PDF EPUB (True) | 28 MB
English | 2023 | ISBN: 9819915996, 981991602X | 521 Pages | PDF EPUB (True) | 28 MB
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 graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions.