Ontology boosted deep learning for disease name extraction from Twitter messages

Ontology boosted deep learning for disease name extraction from Twitter messages

Abstract This paper presents an ontology based deep learning approach for extracting disease names from Twitter messages. The approach relies on simple features obtained via conceptual representations of messages to obtain results that out-perform those from word level models. The significance of th...

Full description

Bibliographic Details
Main Authors: Mark Abraham Magumba, Peter Nabende, Ernest Mwebaze
Format: Article
Language:English
Published: SpringerOpen 2018-09-01
Series:Journal of Big Data
Subjects:
Epidemiology
Twitter
Sentiment analysis
Text classification
Concept ontology
Data mining
Online Access:http://link.springer.com/article/10.1186/s40537-018-0139-2

Internet

http://link.springer.com/article/10.1186/s40537-018-0139-2

Similar Items