Learn More
This paper deals with the automation of ontology building process from HTML pages. Our methodology is based on the complementary use of two approaches. The first approach is based on Aussenac-Gilles methodology and requires feedback from the user to propose and refine concepts and their relationships. The second one exploits Web pages structure and is based(More)
Ontologies provide a common layer which plays a major role in supporting information exchange and sharing. In this paper, we focus on the ontological concept extraction process from HTML documents. In order to improve this process, we propose an unsupervised hierarchical clustering algorithm namely "contextual ontological concept extraction" (COCE) which is(More)
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)
  • Lobna Karoui
  • 2006
A "Context" is an elusive concept, that, it could not be defined automatically by a machine. During the last fifteen years, a strong motivation for research on context appeared in different disciplines such as natural language semantics, linguistics, cognitive psychology and artificial intelligence (AI). In this paper, we focus our attention on the ontology(More)
Ontologies provide a common layer that plays a major role in information exchange and support sharing. Ontologies proliferation relies strongly on the automation of their building, integration and deployment processes. In this paper, we present an integrated framework involving complementary dimensions to drive the (semi) automatic acquisition conceptual(More)
AbstrAct Research in ontology learning had always separated between ontology building and evaluation tasks. Moreover, it had used for example a sentence, a syntactic structure or a set of words to establish the context of a word. However, this research avoids accounting for the structure of the document and the relation between the contexts. In our work, we(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)