scholarly journals Formal concept analysis for an e-learning semantic web

2009 ◽  
Vol 36 (8) ◽  
pp. 10952-10961 ◽  
Author(s):  
Ghassan Beydoun
Keyword(s):  
Semantic Web ◽  
Formal Concept Analysis ◽  
Concept Analysis ◽  
Formal Concept ◽  
E Learning

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.

Critical Analysis on Open Source LMSs using FCA

2013 ◽  
Vol 11 (4) ◽  
pp. 97-111 ◽  
Author(s):  
K. Sumangali ◽  
Ch. Aswani Kumar
Keyword(s):  
Learning Environment ◽  
Open Source ◽  
Formal Concept Analysis ◽  
Critical Analysis ◽  
Management System ◽  
Concept Analysis ◽  
Formal Context ◽  
Formal Concept ◽  
Mathematical Framework ◽  
E Learning

The objective of this paper is to apply Formal Concept Analysis (FCA) to identify the best open source Learning Management System (LMS) for an E-learning environment. FCA is a mathematical framework that represents knowledge derived from a formal context. In constructing the formal context, LMSs are treated as objects and their features as attributes. This context is analysed and classified into concepts based on the rules of FCA. The knowledge derived from the concepts and our analyses reveal that Moodle is exceptional, with more features when compared with other LMSs.

Semantic Web Ontology Integration Based on Formal Concept Analysis

2013 ◽  
Vol 373-375 ◽  
pp. 1714-1718
Author(s):  
Hong Xia
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Formal Concept Analysis ◽  
Service Discovery ◽  
Concept Analysis ◽  
Domain Ontology ◽  
Ontology Engineering ◽  
Formal Concept ◽  
Modeling Concept

Matchmaking is the basis of doing service discovery and composition. Using ontology semantically express the service of capabilities, correctly match service. Domain ontology and Formal Concept Analysis aim at modeling concept. The role of FCA in ontology engineering is supporting reusing independently developed domain ontology. Evaluating concept similarity identifies the different concepts that are semantically close. In this paper, using concept and attribute of web services to construct the ontology. Also, an ontology based method for assessing similarity between FCA concepts is proposed.

CONCEPT SIMILARITY IN FUZZY FORMAL CONCEPT ANALYSIS FOR SEMANTIC WEB

2010 ◽  
Vol 18 (02) ◽  
pp. 153-167 ◽  
Author(s):  
ANNA FORMICA
Keyword(s):  
Semantic Web ◽  
Formal Concept Analysis ◽  
Concept Analysis ◽  
Formal Concept ◽  
Fuzzy Data ◽  
Digital Resources ◽  
Fuzzy Formal Concept ◽  
Fuzzy Formal Concept Analysis ◽  
The Web ◽  
Concept Similarity

This paper presents a method for evaluating concept similarity within Fuzzy Formal Concept Analysis. In the perspective of developing the Semantic Web, such a method can be helpful when the digital resources found on the Internet cannot be treated equally and the integration of fuzzy data becomes fundamental for the search and discovery of information in the Web.

Critical Analysis on Open Source LMSs Using FCA

2015 ◽  
pp. 1111-1125
Author(s):  
K. Sumangali ◽  
Ch. Aswani Kumar
Keyword(s):  
Learning Environment ◽  
Open Source ◽  
Formal Concept Analysis ◽  
Critical Analysis ◽  
Management System ◽  
Concept Analysis ◽  
Formal Context ◽  
Formal Concept ◽  
Mathematical Framework ◽  
E Learning

The objective of this paper is to apply Formal Concept Analysis (FCA) to identify the best open source Learning Management System (LMS) for an E-learning environment. FCA is a mathematical framework that represents knowledge derived from a formal context. In constructing the formal context, LMSs are treated as objects and their features as attributes. This context is analysed and classified into concepts based on the rules of FCA. The knowledge derived from the concepts and our analyses reveal that Moodle is exceptional, with more features when compared with other LMSs.

Using Formal Concept Analysis and Rough Set Constructing the System of Semantic Web

2011 ◽  
Vol 58-60 ◽  
pp. 1664-1670
Author(s):  
Hong Sheng Xu ◽  
Rui Ling Zhang
Keyword(s):  
Semantic Web ◽  
Rough Set ◽  
Formal Concept Analysis ◽  
Rough Set Theory ◽  
Concept Lattice ◽  
Concept Analysis ◽  
Formal Context ◽  
Great Promise ◽  
Formal Concept ◽  
Concept Lattices

Formal concept analysis (FCA) is based on a formalization of the philosophical understanding of a concept as a unit of thought constituted by its extent and intent. The rough set philosophy is founded on the assumption that with every object of the universe of discourse we associate some information. This paper deals with approaches to knowledge reduction in generalized consistent decision formal context. Finally, a new system model of semantic web based on FCA and rough set is proposed, which preserve more structural and featural information of concept lattice. In order to obtain the concept lattices with relatively less attributes and objects, we study the reduction of the concept lattices based on FCA and rough set theory. The experimental results indicate that this method has great promise.

Sign in / Sign up

Export Citation Format

Share Document