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Sentiment Analysis in the Bio-Medical DomainIntroduction

Sentiment Analysis in the Bio-Medical Domain: Introduction [This introductory chapter reviews the general area of sentiment analysis research and posits a case for incorporating commonsense knowledge in machines, as a means to better understand natural language. In particular, the chapter introduces converging paradigms of sentiment analysis and biomedical text mining. Subsequently, a comprehensive literature review of commonsense knowledge representation is presented, together with a discussion on why commonsense is required for sentiment analysis and natural language understanding. Next, the chapter introduces computational creativity and concepts of computation and medical lexicons. Finally, the chapter concludes with a brief discussion of key challenges involved in sentiment analysis.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Sentiment Analysis in the Bio-Medical DomainIntroduction

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Publisher
Springer International Publishing
Copyright
© Springer International Publishing AG 2017
ISBN
978-3-319-68467-3
Pages
1 –19
DOI
10.1007/978-3-319-68468-0_1
Publisher site
See Chapter on Publisher Site

Abstract

[This introductory chapter reviews the general area of sentiment analysis research and posits a case for incorporating commonsense knowledge in machines, as a means to better understand natural language. In particular, the chapter introduces converging paradigms of sentiment analysis and biomedical text mining. Subsequently, a comprehensive literature review of commonsense knowledge representation is presented, together with a discussion on why commonsense is required for sentiment analysis and natural language understanding. Next, the chapter introduces computational creativity and concepts of computation and medical lexicons. Finally, the chapter concludes with a brief discussion of key challenges involved in sentiment analysis.]

Published: Jan 24, 2018

Keywords: Opinion mining; Sentiment analysis; Biomedical text mining; Natural language processing; Deep learning; Computational creativity

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