| Description |
1 online resource (324 pages) : illustrations |
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text file rda |
| Bibliography |
Includes bibliographical references and index. |
| Note |
"A guide to corpus-building for applications"--Book cover. |
| Contents |
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. |
| Summary |
"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"--Provided by publisher. |
| Subject |
Natural language processing (Computer science)
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Corpora (Linguistics) -- Data processing.
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Machine learning.
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Traitement automatique des langues naturelles. |
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Corpus (Linguistique) -- Informatique. |
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Apprentissage automatique. |
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Machine learning |
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Natural language processing (Computer science) |
| Added Author |
Stubbs, Amber, author.
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| Other Form: |
Print version: Pustejovsky, J. (James). Natural language annotation for machine learning. Sebastopol, CA : O'Reilly Media, ©2013 9781449306663 (DLC) 2012289691 (OCoLC)794362649 |
| ISBN |
9781449359768 (electronic book) |
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1449359760 (electronic book) |
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9781449359775 (electronic book) |
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1449359779 (electronic book) |
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(paper) |
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(paper) |
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