Representation Learning for Natural Language Processing - Zhiyuan Liu Yankai Lin Maosong Sun Kartoniert (TB)

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 fo r 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.