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Representation Learning for Natural Language Processing [E-Book] / edited by Zhiyuan Liu, Yankai Lin, Maosong Sun.
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 techniq...
|Personal Name(s):||Lin, Yankai, editor|
|Liu, Zhiyuan, editor / Sun, Maosong, editor|
2nd edition 2023.
XX, 521 pages 169 illustrations in color (online resource)
- Chapter 1. Representation Learning and NLP
- Chapter 2. Word Representation
- Chapter 3. Compositional Semantics
- Chapter 4. Sentence Representation
- Chapter 5. Document Representation
- Chapter 6. Sememe Knowledge Representation
- Chapter 7. World Knowledge Representation
- Chapter 8. Network Representation
- Chapter 9. Cross-Modal Representation
- Chapter 10. Resources
- Chapter 11. Outlook.