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Sentiment Analysis in the Bio-Medical DomainApplication to Sentiment Analysis

Sentiment Analysis in the Bio-Medical Domain: Application to Sentiment Analysis [This chapter illustrates the building and expansion of WordNet for Medical Events (WME) and evaluate its performance. WME has been developed for medical opinion mining and can be used as a standalone medical lexicon. ConceptNet has been used to improve the graphical representation of the underlying architecture in WME. Two methods have been proposed and incorporated to improve the overall performance of the lexicon. First method adds two new features to the existing WME namely affinity and gravity score. To evaluate the new structure, machine learning techniques and linguistic approaches have been incorporated. Finally, the chapter proposes a novel fusion of computational creativity and machine learning.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Sentiment Analysis in the Bio-Medical DomainApplication to Sentiment Analysis

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Publisher
Springer International Publishing
Copyright
© Springer International Publishing AG 2017
ISBN
978-3-319-68467-3
Pages
105 –125
DOI
10.1007/978-3-319-68468-0_4
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter illustrates the building and expansion of WordNet for Medical Events (WME) and evaluate its performance. WME has been developed for medical opinion mining and can be used as a standalone medical lexicon. ConceptNet has been used to improve the graphical representation of the underlying architecture in WME. Two methods have been proposed and incorporated to improve the overall performance of the lexicon. First method adds two new features to the existing WME namely affinity and gravity score. To evaluate the new structure, machine learning techniques and linguistic approaches have been incorporated. Finally, the chapter proposes a novel fusion of computational creativity and machine learning.]

Published: Jan 24, 2018

Keywords: WordNet for medical events; Affinity score; Gravity score; ConceptNet; Hybrid approach; Medical lexicon; Computational creativity; K-means

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