Automatic ontology generation for data mining using fca and clustering

Motivated by the increased need for formalized representations of the domain of Data Mining, the success of using Formal Concept Analysis (FCA) and Ontology in several Computer Science fields, we present in this paper a new approach for automatic generation of Fuzzy Ontology of Data Mining (FODM), through the fusion of conceptual clustering, fuzzy logic, and FCA. In our approach, we propose to generate ontology taking in consideration another degree of granularity into the process of generation. Indeed, we suggest to define an ontology between classes resulting from a preliminary classification on the data. We prove that this approach optimize the definition of the ontology, offered a better interpretation of the data and optimized both the space memory and the execution time for exploiting this data.Comment: 10pages, 8 figures KEOD 2013, accepted but not enregistrement De: KEOD Secretariat [[email protected]] Envoy\'e: mardi 21 mai 2013 10:47 We are happy to inform you that the regular paper you have submitted to KEOD, with number 34, entitled "Automatic Ontology Generation for Data Mining Using FCA and Clustering", has been accepted as a Short Paper. arXiv admin note: text overlap with arXiv:1310.7829 by other author