Overview
- Offers a novel approach to combine computational complexity and machine learning
- Demonstrates a construction of Medical Lexicon for the sole purpose of Sentiment Analysis in Bio-medical Domain
- Includes a special chapter on experimental results obtained on the medical lexicon built
Part of the book series: Socio-Affective Computing (SAC, volume 7)
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Table of contents (5 chapters)
Keywords
About this book
The abundance of text available in social media and health-related forums and blogs have recently attracted the interest of the public health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical domain, i.e., WordNet for Medical Events (WME). This book gives an insight in handling unstructured textual data and converting it to structured machine-processable data in the bio-medical domain.
The readers will discover the following key novelties:
1) development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.;
2) ensemble of machine learning and computational creativity;
3) development of microtext analysis techniques to overcome the inconsistency in social communication.
It will be of interest to researchers in the fields of socially-intelligent human-machine interaction and biomedical text miningAuthors and Affiliations
About the authors
He completed his Bachelor's degree in Computer Science and Engg., from IIIT-Bhubaneswar, India in 2013. He further recieved a M.Tech degree from University of Hyderabad, India in 2016, with majors in Computer Science. During his pursuits of Master's degree, he joined Dr. Cambria's research group SenticNet as an intern, where he worked on bio-medical sentiment analysis. This exposure and a keen-to-learn attitude motivated him to apply for Ph.D under Dr. Cambria.
Bibliographic Information
Book Title: Sentiment Analysis in the Bio-Medical Domain
Book Subtitle: Techniques, Tools, and Applications
Authors: Ranjan Satapathy, Erik Cambria, Amir Hussain
Series Title: Socio-Affective Computing
DOI: https://doi.org/10.1007/978-3-319-68468-0
Publisher: Springer Cham
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2017
Hardcover ISBN: 978-3-319-68467-3Published: 01 February 2018
Softcover ISBN: 978-3-319-88609-1Published: 06 June 2019
eBook ISBN: 978-3-319-68468-0Published: 23 January 2018
Series ISSN: 2509-5706
Series E-ISSN: 2509-5714
Edition Number: 1
Number of Pages: XXIV, 134
Number of Illustrations: 12 b/w illustrations, 33 illustrations in colour
Topics: Biomedicine general, Computational Intelligence, Computer Science, general