Natural language annotation for machine learning / James Pustejovsky and Amber Stubbs.

"Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle—the process of adding metadata to your training...

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Bibliographic Details
Main Author: Pustejovsky, J.
Other Authors: Stubbs, Amber.
Format: Book
Language:English
Published: Sebastopol, CA : O'Reilly Media, ©2013.
Subjects:
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245 1 0 |a Natural language annotation for machine learning /  |c James Pustejovsky and Amber Stubbs. 
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504 |a Includes bibliographical references (pages 303-313) and index. 
505 0 |a The basics -- Defining your goal and dataset -- Corpus analytics -- Building your model and specification -- Applying and adopting annotation standards -- Annotation and adjudication -- Training: machine learning -- Testing and evaluation -- Revising and reporting -- Annotation: TimeML -- Automatic annotation: generating TimeML -- Afterword: the future of annotation. 
520 |a "Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle—the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don’t need any programming or linguistics experience to get started.Using detailed examples at every step, you’ll learn how the MATTER Annotation Development Process helps you Model, Annotate, Train, Test, Evaluate, and Revise your training corpus. You also get a complete walkthrough of a real-world annotation project."--Back cover. 
650 0 |a Natural language processing (Computer science) 
650 0 |a Corpora (Linguistics)  |x Data processing. 
650 0 |a Machine learning. 
690 |a Simmons University authors. Stubbs, Amber.  
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