Multilingual Natural Language Processing Applications

Multilingual Natural Language Processing Applications

  • Daniel Bikel
  • Imed Zitouni
Publisher:IBM PressISBN 13: 9780137047819ISBN 10: 0137047819

Paperback & Hardcover deals ―

Amazon IndiaGOFlipkart GOSnapdealGOSapnaOnlineGOJain Book AgencyGOBooks Wagon₹552Book ChorGOCrosswordGODC BooksGO

e-book & Audiobook deals ―

Amazon India GOGoogle Play Books ₹100.79Audible GO

* Price may vary from time to time.

* GO = We're not able to fetch the price (please check manually visiting the website).

Know about the book -

Multilingual Natural Language Processing Applications is written by Daniel Bikel and published by IBM Press. It's available with International Standard Book Number or ISBN identification 0137047819 (ISBN 10) and 9780137047819 (ISBN 13).

Multilingual Natural Language Processing Applications is the first comprehensive single-source guide to building robust and accurate multilingual NLP systems. Edited by two leading experts, it integrates cutting-edge advances with practical solutions drawn from extensive field experience. Part I introduces the core concepts and theoretical foundations of modern multilingual natural language processing, presenting today’s best practices for understanding word and document structure, analyzing syntax, modeling language, recognizing entailment, and detecting redundancy. Part II thoroughly addresses the practical considerations associated with building real-world applications, including information extraction, machine translation, information retrieval/search, summarization, question answering, distillation, processing pipelines, and more. This book contains important new contributions from leading researchers at IBM, Google, Microsoft, Thomson Reuters, BBN, CMU, University of Edinburgh, University of Washington, University of North Texas, and others. Coverage includes Core NLP problems, and today’s best algorithms for attacking them Processing the diverse morphologies present in the world’s languages Uncovering syntactical structure, parsing semantics, using semantic role labeling, and scoring grammaticality Recognizing inferences, subjectivity, and opinion polarity Managing key algorithmic and design tradeoffs in real-world applications Extracting information via mention detection, coreference resolution, and events Building large-scale systems for machine translation, information retrieval, and summarization Answering complex questions through distillation and other advanced techniques Creating dialog systems that leverage advances in speech recognition, synthesis, and dialog management Constructing common infrastructure for multiple multilingual text processing applications This book will be invaluable for all engineers, software developers, researchers, and graduate students who want to process large quantities of text in multiple languages, in any environment: government, corporate, or academic.