Natural Language Annotation for Machine Learning

Author:   James Pustejovsky ,  Amber Stubbs
Publisher:   O'Reilly Media
Edition:   annotated edition
ISBN:  

9781449306663


Pages:   350
Publication Date:   04 December 2012
Format:   Paperback
Availability:   In Print   Availability explained
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Natural Language Annotation for Machine Learning


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Author:   James Pustejovsky ,  Amber Stubbs
Publisher:   O'Reilly Media
Imprint:   O'Reilly Media
Edition:   annotated edition
Dimensions:   Width: 17.80cm , Height: 1.90cm , Length: 23.30cm
Weight:   0.549kg
ISBN:  

9781449306663


ISBN 10:   1449306667
Pages:   350
Publication Date:   04 December 2012
Audience:   Professional and scholarly ,  General/trade ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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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/.

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