scholarly journals Combining Semantic Web Technologies with Evolving Fuzzy Classifier eClass for EHR-Based Phenotyping: A Feasibility Study

2014 ◽  
pp. 195-208
Author(s):  
M. Arguello ◽  
S. Lekkas ◽  
J. Des ◽  
M.J. Fernandez-Prieto ◽  
L. Mikhailov
Keyword(s):  
Semantic Web ◽  
Feasibility Study ◽  
Fuzzy Classifier ◽  
Semantic Web Technologies ◽  
Web Technologies

Semantic Web Technologies for e-Learning: Models and Implementation

Informatica ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Valentina Dagienė ◽  
Daina Gudonienė ◽  
Renata Burbaitė
Keyword(s):  
Semantic Web ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
E Learning

Applying Semantic Web Technologies to Drug Safety Determination

2006 ◽  
Vol 21 (1) ◽  
pp. 82-86 ◽  
Author(s):  
S. Stephens ◽  
A. Morales ◽  
M. Quinlan
Keyword(s):  
Semantic Web ◽  
Drug Safety ◽  
Semantic Web Technologies ◽  
Web Technologies

How Industry 4.0 Can Benefit From Semantic Web Technologies and Artefacts

2021 ◽  
Vol 13 (4) ◽  
pp. 64-74
Author(s):  
Leila Zemmouchi-Ghomari
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Semantic Web ◽  
Industry 4.0 ◽  
The Internet ◽  
Time Data ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Real Time Data ◽  
The Internet Of Things

Industry 4.0 is a technology-driven manufacturing process that heavily relies on technologies, such as the internet of things (IoT), cloud computing, web services, and big real-time data. Industry 4.0 has significant potential if the challenges currently being faced by introducing these technologies are effectively addressed. Some of these challenges consist of deficiencies in terms of interoperability and standardization. Semantic Web technologies can provide useful solutions for several problems in this new industrial era, such as systems integration and consistency checks of data processing and equipment assemblies and connections. This paper discusses what contribution the Semantic Web can make to Industry 4.0.

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