Flexible Simulation e-Learning Environment for Studying Digital Circuits and Possibilities for it Deployment as Semantic Web Service

2011 ◽  
Vol 39 (4) ◽  
pp. 349-369 ◽  
Author(s):  
P. Radoyska ◽  
T. Ivanova ◽  
N. Spasova
Keyword(s):  
Learning Environment ◽  
Semantic Web ◽  
Web Service ◽  
Digital Circuits ◽  
Semantic Web Service ◽  
E Learning

Discovery Mechanism for Learning Semantic Web Service

Web Services ◽  
2019 ◽  
pp. 575-596
Author(s):  
Chaker Ben Mahmoud ◽  
Ikbel Azaiez ◽  
Fathia Bettahar ◽  
Faiez Gargouri
Keyword(s):  
Semantic Web ◽  
Web Service ◽  
Learning Style ◽  
Learning Objects ◽  
Learning Object ◽  
Traditional Learning ◽  
Semantic Web Service ◽  
Learning Intention ◽  
Learning Path ◽  
E Learning

Nowadays, e-learning offers advantages over traditional learning in terms of independence. Moreover, adaptive e-learning systems take into account learner's profile, such as learning style and level of knowledge, in order to provide the most appropriate learning object. However, the essential challenge is finding and identifying the learning objects from a big corpus while ensuring their independence in different contexts. To overcome these problems of interoperability and accessibility of learning objects, the authors proposed to define a learning semantic Web service for each learning object. This service is an extension of OWLS that encompasses the description of the learning intention and the use of context that characterize a learning object. In this paper, the authors propose a new discovery mechanism based on learning intention and context use guided by the learner's intention and profile in order to offer a personalized learning path. Experimental results prove the efficiency of the proposed approach and approve its notable contribution.

Discovery Mechanism for Learning Semantic Web Service

2016 ◽  
Vol 12 (1) ◽  
pp. 23-43 ◽  
Author(s):  
Chaker Ben Mahmoud ◽  
Ikbel Azaiez ◽  
Fathia Bettahar ◽  
Faiez Gargouri
Keyword(s):  
Semantic Web ◽  
Web Service ◽  
Learning Style ◽  
Learning Objects ◽  
Learning Object ◽  
Traditional Learning ◽  
Semantic Web Service ◽  
Learning Intention ◽  
Learning Path ◽  
E Learning

Nowadays, e-learning offers advantages over traditional learning in terms of independence. Moreover, adaptive e-learning systems take into account learner's profile, such as learning style and level of knowledge, in order to provide the most appropriate learning object. However, the essential challenge is finding and identifying the learning objects from a big corpus while ensuring their independence in different contexts. To overcome these problems of interoperability and accessibility of learning objects, the authors proposed to define a learning semantic Web service for each learning object. This service is an extension of OWLS that encompasses the description of the learning intention and the use of context that characterize a learning object. In this paper, the authors propose a new discovery mechanism based on learning intention and context use guided by the learner's intention and profile in order to offer a personalized learning path. Experimental results prove the efficiency of the proposed approach and approve its notable contribution.

The Research of Semantic Web Service Matching Algorithm Based on the Formal Concept Analysis

2013 ◽  
Vol 760-762 ◽  
pp. 1708-1712
Author(s):  
Ying Fang Li ◽  
Ying Jiang Li ◽  
Yan Li ◽  
Yang Bo
Keyword(s):  
Semantic Web ◽  
Web Service ◽  
Formal Concept Analysis ◽  
Service Discovery ◽  
Concept Lattice ◽  
Concept Analysis ◽  
Formal Concept ◽  
Semantic Web Service ◽  
Matching Algorithm ◽  
Service Matching

At present, as the number of web services resources on the network drastically increased, how to quickly and efficiently find the needed services from publishing services has become a problem to resolve. Aiming at the problems of low efficiency in service discovery of traditional web service, the formal concept analysis ( FCA) is introduced into the semantic Web service matching, and a Matching Algorithm based semantic web service is proposed. With considering the concept of limited inheritance,this method introduces the concept of limited inheritance to the semantic similarity calculation based on the concept lattice. It is significant in enhancing the service function matching in practical applications through adjust the calculation.

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