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Natural Language Annotation for Machine Learning

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ISBN-10: 1449306667

ISBN-13: 9781449306663

Edition: 2012

Authors: James Pustejovsky, Amber Stubbs

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Description:

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…    
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Book details

Copyright year: 2012
Publisher: O'Reilly Media, Incorporated
Publication date: 11/2/2012
Binding: Paperback
Pages: 346
Size: 7.00" wide x 9.25" long x 0.75" tall
Weight: 1.496
Language: English

Amber Stubbs is a Ph.D. candidate in Computer Science at Brandeis University in the Laboratory for Linguistics and Computation. Her dissertation is focused on creating an annotation methodology to aid in extracting high-level information from natural language files, particularly biomedical texts. Information about her publications and other projects can be found on her website: http://pages.cs.brandeis.edu/~astubbs/ .