Sentiment Analysis in the Bio-Medical Domain
Techniques, Tools, and Applications
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Computer Science, Health & Well Being, Medical
| Author: | Erik Cambria, Amir Hussain, Ranjan Satapathy | ISBN: | 9783319684680 |
| Publisher: | Springer International Publishing | Publication: | January 23, 2018 |
| Imprint: | Springer | Language: | English |
| Author: | Erik Cambria, Amir Hussain, Ranjan Satapathy |
| ISBN: | 9783319684680 |
| Publisher: | Springer International Publishing |
| Publication: | January 23, 2018 |
| Imprint: | Springer |
| Language: | English |
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:
-
development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.;
-
ensemble of machine learning and computational creativity;
-
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 mining
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:
-
development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.;
-
ensemble of machine learning and computational creativity;
-
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 mining
