Paper Info
Title
Type-2 fuzzy ontology-aided recommendation systems for IoT-based healthcare.
Abstract
•The available healthcare systems are imperfect to extract precise physiological information of patients.•The classical ontologies are unable to recommend diets without knowing the current condition of a patient.•Wearable sensors with type-2 fuzzy logic efficiently monitor the patient's body.•Fuzzy ontology-based knowledge precisely suggests diabetes-specific prescriptions.•Type-2 fuzzy ontology significantly increases the prediction accuracy of a patient's condition.
Year
DOI
Venue
2018
10.1016/j.comcom.2017.10.005
Computer Communications
Keywords
Field
DocType
Semantic knowledge,Remotely monitoring,Type-2 fuzzy ontology,Iot-based healthcare,Recommendation system
Ontology,Protégé,RDF query language,Information retrieval,Computer science,Fuzzy logic,Description logic,Knowledge management,Computer network,SPARQL,Semantic Web Rule Language,Web Ontology Language
Journal
Volume
ISSN
Citations 
119
0140-3664
13
PageRank 
References 
Authors
0.59
30
7
Name
Order
Citations
PageRank
Farman Ali1816.60
S. M. Islam220013.80
Daehan Kwak335317.45
Pervez Khan419416.72
Niamat Ullah521514.45
Sang-jo Yoo622527.74
Kyung Sup Kwak79212.10