EAN: 9789811555756

REPRESENTATION LEARNING FOR NATURAL LANGUAGE PR...

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 for 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.

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