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(Ebook) Natural Language Annotation for Machine Learning: A guide to corpus-building for applications by James Pustejovsky, Amber Stubbs ISBN 9781449306663, 1449306667

  • SKU: EBN-2561356
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Authors:James Pustejovsky, Amber Stubbs
Pages:97 pages.
Year:2012
Editon:Early Release
Publisher:O'Reilly Media
Language:english
File Size:2.13 MB
Format:pdf
ISBNS:9781449306663, 1449306667
Categories: Ebooks

Product desciption

(Ebook) Natural Language Annotation for Machine Learning: A guide to corpus-building for applications by James Pustejovsky, Amber Stubbs ISBN 9781449306663, 1449306667

Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process.
Systems exist for analyzing existing corpora, but making a new corpus can be extremely complex. To help you build a foundation for your own machine learning goals, this easy-to-use guide includes case studies that demonstrate four different annotation tasks in detail. You’ll also learn how to use a lightweight software package for annotating texts and adjudicating the annotations.
This book is a perfect companion to O'Reilly’s Natural Language Processing with Python, which describes how to use existing corpora with the Natural Language Toolkit.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

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