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An Extension of Protege for an Automatic Fuzzy-Ontology Building Using Clustering and FCA


Affiliations
1 Universite Tunis El Manar, Ecole Nationale d'Ingenieurs de Tunis, LRSITI, Tunis, Tunisia
2 Universite Tunis El Manar, Faculte des Sciences de Tunis, LIPAH, Tunis, Tunisia
 

The process of building ontology is a very complex and time-consuming process especially when dealing with huge amount of data. Unfortunately current marketed tools are very limited and don't meet all user needs. Indeed, these software build the core of the ontology from initial data that generates a big number of information. In this paper, we aim to resolve these problems by adding an extension to the well known ontology editor Protege in order to work towards a complete FCA-based framework which resolves the limitation of other tools in building fuzzy-ontology. We will give, in this paper, some details on our semiautomatic collaborative tool called FOD Tab Plug-in which takes into consideration another degree of granularity in the process of generation. In fact, it follows a bottom-up strategy based on conceptual clustering, fuzzy logic and Formal Concept Analysis (FCA) and it defines ontology between classes resulting from a preliminary classification of data and not from the initial large amount of data.

Keywords

Formal Concept Analysis, Fuzzy Logic, Ontology extraction, Protege-200.
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  • An Extension of Protege for an Automatic Fuzzy-Ontology Building Using Clustering and FCA

Abstract Views: 195  |  PDF Views: 131

Authors

Aloui Amira
Universite Tunis El Manar, Ecole Nationale d'Ingenieurs de Tunis, LRSITI, Tunis, Tunisia
Grissa Touzi Amel
Universite Tunis El Manar, Faculte des Sciences de Tunis, LIPAH, Tunis, Tunisia

Abstract


The process of building ontology is a very complex and time-consuming process especially when dealing with huge amount of data. Unfortunately current marketed tools are very limited and don't meet all user needs. Indeed, these software build the core of the ontology from initial data that generates a big number of information. In this paper, we aim to resolve these problems by adding an extension to the well known ontology editor Protege in order to work towards a complete FCA-based framework which resolves the limitation of other tools in building fuzzy-ontology. We will give, in this paper, some details on our semiautomatic collaborative tool called FOD Tab Plug-in which takes into consideration another degree of granularity in the process of generation. In fact, it follows a bottom-up strategy based on conceptual clustering, fuzzy logic and Formal Concept Analysis (FCA) and it defines ontology between classes resulting from a preliminary classification of data and not from the initial large amount of data.

Keywords


Formal Concept Analysis, Fuzzy Logic, Ontology extraction, Protege-200.