Natural Language Annotation for Machine Learning
A Guide to Corpus-Building for Applications
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.
| Details | |
|---|---|
| Herausgeber | O'Reilly Media |
| Autor(en) | James Pustejovsky, Amber Stubbs |
| ISBN | 978-1-4493-0666-3 |
| veröffentlicht | 2012 |
| Seiten | 350 |
| Sprache | English |




