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 mining
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 mining
Produkteigenschaften
- Artikelnummer: 9783319684673
- Medium: Buch
- ISBN: 978-3-319-68467-3
- Verlag: Springer International Publishing
- Erscheinungstermin: 01.02.2018
- Sprache(n): Englisch
- Auflage: 1. Auflage 2017
- Serie: Socio-Affective Computing
- Produktform: Gebunden, HC runder Rücken kaschiert
- Gewicht: 442 g
- Seiten: 134
- Format (B x H x T): 160 x 241 x 14 mm
- Ausgabetyp: Kein, Unbekannt