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

By: Contributor(s): Material type: TextTextPublication details: Beijing, China : O'Reilly Media, Incorporated, c2013Description: xiv, 324 pages : illustrations ; 23 cmISBN:
  • 9781449306663
Subject(s): LOC classification:
  • QA 76.9.N38 .P87 2013
Contents:
1. The Basics -- 2. Defining your goal and dataset -- 3. Corpus analytics -- 4. Building your model and specification -- 5. Applying and adopting annotation standards -- 6. Annotation and adjudication -- 7. Training : machine learning -- 8. Testing and evaluation -- 9. Revising and reporting -- 10. Annotation : TimeML -- 11. Automatic annotation : generating TimeML -- 12. Afterword : the future of annotation.
Summary: This book is intended as a resource for people who are interested in using computers to help process natural language.
Item type: Books
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Holdings
Item type Current library Home library Collection Call number Copy number Status Date due Barcode
Books Books National University - Manila LRC - Graduate Studies General Circulation Gen. Ed. - CCIT GC QA 76.9.N38 .P87 2013 (Browse shelf(Opens below)) c.1 Available NULIB000009215

Includes bibliographical references and index.

1. The Basics -- 2. Defining your goal and dataset -- 3. Corpus analytics -- 4. Building your model and specification -- 5. Applying and adopting annotation standards -- 6. Annotation and adjudication -- 7. Training : machine learning -- 8. Testing and evaluation -- 9. Revising and reporting -- 10. Annotation : TimeML -- 11. Automatic annotation : generating TimeML -- 12. Afterword : the future of annotation.

This book is intended as a resource for people who are interested in using computers to help process natural language.

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