ranjan satapathy (5 Ergebnisse)

Paperback. Zustand: Brand New. 208 pages. 8.66x5.91x0.47 inches. In Stock.

Taschenbuch. Zustand: Neu. Sentiment Analysis in the Bio-Medical Domain | Techniques, Tools, and Applications | Ranjan Satapathy (u. a.) | Taschenbuch | Socio-Affective Computing | xxiv | Englisch | 2019 | Springer | EAN 9783319886091 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: New.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.