Lobna Karoui

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In this paper, we focus on the ontological concept extraction and evaluation process from HTML documents. In order to improve this process, we propose an unsupervised hierarchical clustering algorithm namely " Contextual Concept Discovery " (CCD) which is an incremental use of the partitioning algorithm Kmeans and is guided by a structural context. Our(More)
Un des problèmes majeurs dans la gestion des ontologies est son éva-luation. Cet article traite l'évaluation des concepts ontologiques qui sont ex-traits de pages Web. Pour cela, nous avons proposé une méthodologie d'évaluation des concepts basée trois critères révélateurs : « le degré de crédi-bilité »; « le degré de cohésion » et « le degré d'éligibilité(More)
Relation extraction is a difficult open research problem with important applications in several fields such as knowledge management, web mining, ontology building, intelligent systems, etc. In our research, we focus on extracting relations among the ontological concepts in order to build a domain ontology. In this paper, firstly, we answer some crucial(More)
I. Abstract—Ontological concept evaluation is a difficult task. Till now, it is done either by domain expert or a knowledge base (thesaurus, ontology, etc.). In this research, we propose a new evaluation method based on a large web document collection, several context definitions deduced from it and three criteria. It provides a support for either a domain(More)