Sentiment Analysis in the Bio-Medical Domain / Socio-Affective Computing Bd.7 (PDF)
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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 miningHe 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.
- Autoren: Ranjan Satapathy , Erik Cambria , Amir Hussain
- 2018, 1st ed. 2017, 134 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 331968468X
- ISBN-13: 9783319684680
- Erscheinungsdatum: 23.01.2018
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Grösse: 3.82 MB
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