scholarly journals Social and Semantic Web Technologies for the Text-to-Knowledge Translation Process in Biomedicine

10.5772/13560 ◽  
2011 ◽  
Author(s):  
Carlos Cano ◽  
Alberto Labarga ◽  
Armando Blanco ◽  
Leonid Peshki
Keyword(s):  
Semantic Web ◽  
Knowledge Translation ◽  
Translation Process ◽  
Semantic Web Technologies ◽  
Web Technologies

scholarly journals Towards Verbalizing SPARQL Queries in Arabic

2016 ◽  
Vol 6 (2) ◽  
pp. 937-944
Author(s):  
I. Al Agha ◽  
O. El-Radie
Keyword(s):  
Semantic Web ◽  
Natural Language ◽  
Query Language ◽  
Arabic Language ◽  
Syntactic Analysis ◽  
Information Need ◽  
Translation Process ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Different Characteristics

With the wide spread of Open Linked Data and Semantic Web technologies, a larger amount of data has been published on the Web in the RDF and OWL formats. This data can be queried using SPARQL, the Semantic Web Query Language. SPARQL cannot be understood by ordinary users and is not directly accessible to humans, and thus they will not be able to check whether the retrieved answers truly correspond to the intended information need. Driven by this challenge, natural language generation from SPARQL data has recently attracted a considerable attention. However, most existing solutions to verbalize SPARQL in natural language focused on English and Latin-based languages. Little effort has been made on the Arabic language which has different characteristics and morphology. This work aims to particularly help Arab users to perceive SPARQL queries on the Semantic Web by translating SPARQL to Arabic. It proposes an approach that gets a SPARQL query as an input and generates a query expressed in Arabic as an output. The translation process combines both morpho-syntactic analysis and language dependencies to generate a legible and understandable Arabic query. The approach was preliminary assessed with a sample query set, and results indicated that 75% of the queries were correctly translated into Arabic.

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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