Natural Language Annotation for Machine Learning | Agenda Bookshop Skip to content
Please note that books with a 10-20 working days delivery time may not arrive before Christmas.
Please note that books with a 10-20 working days delivery time may not arrive before Christmas.
A01=James Pustejovsky
A32=Amber Stubbs
Age Group_Uncategorized
Age Group_Uncategorized
Author_James Pustejovsky
automatic-update
Category1=Non-Fiction
Category=UYQL
COP=United States
Delivery_Delivery within 10-20 working days
Inc
Language_English
PA=Available
Price_€20 to €50
PS=Active
softlaunch
USA
5%
off
9781449306663.jpg

Natural Language Annotation for Machine Learning

★★★★★
★★★★★

English

By (author): James Pustejovsky

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. This book is a perfect companion to O'Reilly's Natural Language Processing with Python, which describes how to use existing corpora with the Natural Language Toolkit. See more
€29.44
€30.99
Save 5%
A01=James PustejovskyA32=Amber StubbsAge Group_UncategorizedAuthor_James Pustejovskyautomatic-updateCategory1=Non-FictionCategory=UYQLCOP=United StatesDelivery_Delivery within 10-20 working daysIncLanguage_EnglishPA=AvailablePrice_€20 to €50PS=ActivesoftlaunchUSA
Delivery/Collection within 10-20 working days
Product Details
  • Publication Date: 04 Dec 2012
  • Publisher: O'Reilly Media
  • Publication City/Country: United States
  • Language: English
  • ISBN13: 9781449306663

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 ISO standard for time annotation ISO-TimeML. He is currently heading the development of a standard for annotating spatial information in language. More information on publications and research activities can be found at his webpage: pusto.com. Amber Stubbs is a Ph.D. candidate in Computer Science at Brandeis University in the Laboratory for Linguistics and Computation. Her dissertation is focused on creating an annotation methodology to aid in extracting high-level information from natural language files particularly biomedical texts. Information about her publications and other projects can be found on her website: http://pages.cs.brandeis.edu/~astubbs/.

Customer Reviews

Be the first to write a review
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)
We use cookies to ensure that we give you the best experience on our website. If you continue we'll assume that you are understand this. Learn more
Accept