| 书目名称 | Representation Learning for Natural Language Processing | | 编辑 | Zhiyuan Liu,Yankai Lin,Maosong Sun | | 视频video | | | 概述 | Provides a comprehensive overview of the representation learning techniques for natural language processing.Presents a self-contained reference resource with a rich blend of theory, algorithms and app | | 图书封面 |  | | 描述 | .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..The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, socialnetwork analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lec | | 出版日期 | Book‘‘‘‘‘‘‘‘ 2023Latest edition | | 关键词 | Open Access; Deep Learning; Representation Learning; Knowledge Representation; Word Representation; Docum | | 版次 | 2 | | doi | https://doi.org/10.1007/978-981-99-1600-9 | | isbn_softcover | 978-981-99-1602-3 | | isbn_ebook | 978-981-99-1600-9 | | copyright | The Editor(s) (if applicable) and The Author(s) 2023 |
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发表于 2025-3-21 18:35:19
