Biomedical Natural Language Processing
Author:   Kevin Bretonnel Cohen (University of Colorado, School of Medicine) ,  Dina Demner-Fushman (National Library of Medicine)
Publisher:   John Benjamins Publishing Co
Volume:   11
ISBN:  

9789027249982


Pages:   160
Publication Date:   27 February 2014
Format:   Paperback
Availability:   Available To Order   Availability explained
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Biomedical Natural Language Processing


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Overview

Biomedical Natural Language Processing is a comprehensive tour through the classic and current work in the field. It discusses all subjects from both a rule-based and a machine learning approach, and also describes each subject from the perspective of both biological science and clinical medicine. The intended audience is readers who already have a background in natural language processing, but a clear introduction makes it accessible to readers from the fields of bioinformatics and computational biology, as well. The book is suitable as a reference, as well as a text for advanced courses in biomedical natural language processing and text mining.

Full Product Details

Author:   Kevin Bretonnel Cohen (University of Colorado, School of Medicine) ,  Dina Demner-Fushman (National Library of Medicine)
Publisher:   John Benjamins Publishing Co
Imprint:   John Benjamins Publishing Co
Volume:   11
Weight:   0.320kg
ISBN:  

9789027249982


ISBN 10:   9027249989
Pages:   160
Publication Date:   27 February 2014
Audience:   Professional and scholarly ,  Professional and scholarly ,  Professional & Vocational ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

1. Acknowledgments; 2. List of figures; 3. 1. Introduction to natural language processing; 4. 2. Historical background; 5. 3. Named entity recognition; 6. 4. Relation extraction; 7. 5. Information retrieval/document classification; 8. 6. Concept normalization; 9. 7. Ontologies and computational lexical semantics; 10. 8. Summarization; 11. 9. Question-answering; 12. 10. Software engineering; 13. 11. Corpus construction and annotation; 14. References; 15. Index

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