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:  

9789027249975


Pages:   160
Publication Date:   27 February 2014
Format:   Hardback
Availability:   In stock   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:   0.465kg
ISBN:  

9789027249975


ISBN 10:   9027249970
Pages:   160
Publication Date:   27 February 2014
Audience:   Professional and scholarly ,  Professional and scholarly ,  Professional & Vocational ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In stock   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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