×


 x 

Shopping cart
6%OFFJames Pustejovsky - Natural Language Annotation for Machine Learning - 9781449306663 - V9781449306663
Stock image for illustration purposes only - book cover, edition or condition may vary.

Natural Language Annotation for Machine Learning

€ 43.99
€ 41.37
You save € 2.62!
FREE Delivery in Ireland
Description for Natural Language Annotation for Machine Learning Paperback. 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. Num Pages: 346 pages, Illustrations. BIC Classification: UYQL. Category: (XV) Technical / Manuals. Dimension: 233 x 179 x 19. Weight in Grams: 560.
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 ... Read more

Product Details

Publisher
O´Reilly Media United States
Number of pages
346
Format
Paperback
Publication date
2012
Condition
New
Weight
593g
Number of Pages
350
Place of Publication
Sebastopol, United States
ISBN
9781449306663
SKU
V9781449306663
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-1

About James Pustejovsky
James Pustejovsky teaches and does research in Artificial Intelligence and Computational Linguistics in the Computer Science Department at Brandeis University. His main areas of interest include: lexical meaning, computational semantics, temporal and spatial reasoning, and corpus linguistics. He is active in the development of standards for interoperability between language processing applications, and lead the creation of the recently adopted ... Read more

Reviews for Natural Language Annotation for Machine Learning

Goodreads reviews for Natural Language Annotation for Machine Learning


Subscribe to our newsletter

News on special offers, signed editions & more!