rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Deep Learning in Natural Language Processing
  name:
    name part: Deng, Li.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Liu, Yang.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVII, 329 p. online resource.
  abstract: 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. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing. .
  table of contents: Chapter 1: A Joint Introduction to Natural Language Processing and to Deep Learning -- Chapter 2: Deep Learning in Conversational Language Understanding -- Chapter 3: Deep Learning in Spoken and Text-Based Dialogue Systems -- Chapter 4: Deep Learning in Lexical Analysis and Parsing -- Chapter 5: Deep Learning in Knowledge Graph -- Chapter 6: Deep Learning in Machine Translation -- Chapter 7: Deep Learning in Question Answering -- Chapter 8: Deep Learning in Sentiment Analysis -- Chapter 9: Deep Learning in Social Computing -- Chapter 10: Deep Learning in Natural Language Generation from Images -- 11. Epilogue: Frontiers of NLP in the Deep Learning Era.
  note: edited by Li Deng, Yang Liu.
  subject:
    topic: Artificial intelligence
  subject:
    topic: Natural language processing (Computer science)
  subject:
    topic: Mathematical statistics
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Natural Language Processing (NLP)
  subject:
    topic: Probability and Statistics in Computer Science
  subject:
    topic: Natural Language Processing (NLP)
  classification: Q334-342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  identifier: 9789811052095
  identifier: https://doi.org/10.1007/978-981-10-5209-5
  record info:
    record creation date: 180523
    record change date: 20191220125546.0
    record identifier: 978-981-10-5209-5