Studies in Computational Intelligence

Neural Representations of Natural Language

Authors: White, L., Togneri, R., Liu, W., Bennamoun, M.

  • Enriches readers’ understanding of how neural networks create a machine interpretable representation of the meaning of natural language
  • Absolutely packed with useful insights drawn from experience using and implementing these algorithms
  • Includes two introductory chapters on neural networks, allowing novice readers to quickly understand how machine learning is revolutionizing the field of natural language processing
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書籍の購入

イーブック ¥6,375
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-981-13-0062-2
  • ウォーターマーク付、 DRMフリー
  • ファイル形式: EPUB, PDF
  • どの電子書籍リーダーからでもすぐにお読みいただけます。
  • ご購入後、すぐにダウンロードしていただけます。
ハードカバー ¥7,969
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-981-13-0061-5
  • 個人のお客様には、世界中どこでも配送料無料でお届けします。
  • Usually dispatched within 3 to 5 business days.
この書籍について

This book offers an introduction to modern natural language processing using machine learning, focusing on how neural networks create a machine interpretable representation of the meaning of natural language. Language is crucially linked to ideas – as Webster’s 1923 “English Composition and Literature” puts it: “A sentence is a group of words expressing a complete thought”. Thus the representation of sentences and the words that make them up is vital in advancing artificial intelligence and other “smart” systems currently being developed. Providing an overview of the research in the area, from Bengio et al.’s seminal work on a “Neural Probabilistic Language Model” in 2003, to the latest techniques, this book enables readers to gain an understanding of how the techniques are related and what is best for their purposes. As well as a introduction to neural networks in general and recurrent neural networks in particular, this book details the methods used for representing words, senses of words, and larger structures such as sentences or documents. The book highlights practical implementations and discusses many aspects that are often overlooked or misunderstood. The book includes thorough instruction on challenging areas such as hierarchical softmax and negative sampling, to ensure the reader fully and easily understands the details of how the algorithms function. Combining practical aspects with a more traditional review of the literature, it is directly applicable to a broad readership. It is an invaluable introduction for early graduate students working in natural language processing; a trustworthy guide for industry developers wishing to make use of recent innovations; and a sturdy bridge for researchers already familiar with linguistics or machine learning wishing to understand the other.


Table of contents (6 chapters)

  • Introduction to Neural Networks for Machine Learning

    White, Lyndon (et al.)

    Pages 1-21

    Preview Buy Chapter ¥3,412
  • Recurrent Neural Networks for Sequential Processing

    White, Lyndon (et al.)

    Pages 23-36

    Preview Buy Chapter ¥3,412
  • Word Representations

    White, Lyndon (et al.)

    Pages 37-71

    Preview Buy Chapter ¥3,412
  • Word Sense Representations

    White, Lyndon (et al.)

    Pages 73-92

    Preview Buy Chapter ¥3,412
  • Sentence Representations and Beyond

    White, Lyndon (et al.)

    Pages 93-114

    Preview Buy Chapter ¥3,412

書籍の購入

イーブック ¥6,375
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-981-13-0062-2
  • ウォーターマーク付、 DRMフリー
  • ファイル形式: EPUB, PDF
  • どの電子書籍リーダーからでもすぐにお読みいただけます。
  • ご購入後、すぐにダウンロードしていただけます。
ハードカバー ¥7,969
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-981-13-0061-5
  • 個人のお客様には、世界中どこでも配送料無料でお届けします。
  • Usually dispatched within 3 to 5 business days.
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書誌情報

Bibliographic Information
Book Title
Neural Representations of Natural Language
Authors
Series Title
Studies in Computational Intelligence
Series Volume
783
Copyright
2019
Publisher
Springer Singapore
Copyright Holder
Springer Nature Singapore Pte Ltd.
イーブック ISBN
978-981-13-0062-2
DOI
10.1007/978-981-13-0062-2
ハードカバー ISBN
978-981-13-0061-5
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XIV, 122
Number of Illustrations
5 b/w illustrations, 31 illustrations in colour
Topics