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首页Deep Learning in Natural Language Processing 邓力 - 英文、文字、带目录版本
In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence.
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Deep Learning
in Natural
Language
Processing
Li Deng · Yang Liu Editors
Deep Learning in Natural Language Processing
Li Deng
•
Yang Liu
Editors
Deep Learning in Natural
Language Processing
123
Editors
Li Deng
AI Research at Citadel
Chicago, IL
USA
and
AI Research at Citadel
Seattle, WA
USA
Yang Liu
Tsinghua University
Beijing
China
ISBN 978-981-10-5208-8 ISBN 978-981-10-5209-5 (eBook)
https://doi.org/10.1007/978-981-10-5209-5
Library of Congress Control Number: 2018934459
© Springer Nature Singapore Pte Ltd. 2018
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part
of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,
recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission
or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar
methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this
publication does not imply, even in the absence of a specific statement, that such names are exempt from
the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this
book are believed to be true and accurate at the date of publication. Neither the publisher nor the
authors or the editors give a warranty, express or implied, with respect to the material contained herein or
for any errors or omissions that may have been made. The publisher remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
Printed on acid-free paper
This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd.
part of Springer Nature
The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721,
Singapore
Foreword
“Written by a group of the most active researchers in the field, led by Dr. Deng, an
internationally respected expert in both NLP and deep learning, this book provides
a comprehensive introduction to and up-to-date review of the state of art in applying
deep learning to solve fundamental problems in NLP. Further, the book is highly
timely, as demands for high-quality and up-to-date textbooks and research refer-
ences have risen dramatically in response to the tremendous strides in deep learning
applications to NLP. The boo k offers a unique reference guide for practitioners in
various sectors, especially the Inter net and AI start-ups, where NLP technologies
are becoming an essential enabler and a core differentiator.”
Hongjiang Zhang (Founder, Sourcecode Capital; former CEO of KingSoft)
“This book provides a comprehensive introduction to the latest advances in deep
learning applied to NLP. Written by experienced and aspiring deep learning and
NLP researchers, it covers a broad range of major NLP applications, including
spoken language understanding, dialog systems, lexical analysis, parsing, knowl-
edge graph, machine translation, question answering, sentiment analysis, and social
computing.
The book is clearly structured and moves from major research trends, to the
latest deep learning approaches, to their limitations and promising future work.
Given its self-contained content, sophisticated algorithms, and detailed use cases,
the book offers a valuable guide for all readers who are working on or learning
about deep learning and NLP.”
Haifeng Wang (Vice President and Head of Research, Baidu; former President
of ACL)
“In 2011, at the dawn of deep learning in industry, I estimated that in most speech
recognition applications, computers still made 5 to 10 times more errors than human
subjects, and highlighted the importance of knowledge engineering in future
directions. Within only a handful of years since, deep learning has nearly closed the
gap in the accuracy of conversational speech recognition between human and
computers. Edited and written by Dr. Li Deng—a pioneer in the recent speech
v
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