MIRACL Laboratory Faculty of Economic Sciences and Management of Sfax Route de l’Aéroport Km 4 - BP 1088,3018, Sfax Sfax University, Tunisia
Institut Préparatoire aux Etudes d'Ingénieurs de Sfax IPEIS - Route Menzel Chaker Km 0,5 - BP 1172-3018 Sfax, Tunisia.
feten.baccarb@gmail.com
Assistant Professor of computer science at Preparatory Institute for Engineering Studies, Sfax (Institut Préparatoire aux Etudes d'Ingénieurs de Sfax-IPEIS), Tunisia. Computer Science Engineer and PhD Student, Member of MIRACL Laboratory (Multimedia Information & Advanced Computing Laboratory), University of Sfax-Tunisia. Feten Baccar Ben Amar received an Engineering degree in computer science in 2006 from the National Engineering School of Sfax University (Tunisia), and a Master degree in computer science in 2008 from the Faculty of Economic Sciences and Management of Sfax University (Tunisia). Since 2009, she is preparing her PhD in computer science (PhD completed (expected): fall 2012) . Her research is focused on ontology building from LMF-standardized dictionaries (ISO-24613) and Natural Language Processing (NLP) with particular interset to the Arabic language.
Abstract: In this chapter, the authors propose an approach for generating domain ontologies from LMF standardized dictionaries (ISO-24613). It consists, firstly, of deriving the target ontology core systematically from the explicit information of the LMF dictionary structure. Secondly, it aims at enriching such a core, taking advantage of textual sources with guided semantic fields available in the definitions and the examples of lexical entries. The originality of this work lies not only in the use of a unique and finely-structured source containing multi-domain and lexical knowledge of morphological, syntactic, and semantic levels, lending itself to ontological interpretations, but also in providing ontological elements with linguistic grounding. In addition, the proposed approach has addressed the quality issue that is of a major importance in ontology engineering. They have integrated a validation stage along with the extraction modules in order to maintain the consistency of the generated ontologies. Furthermore, the proposed approach was applied to a case study in the field of astronomy and the experiment has been carried out on the Arabic language. This choice is explained both by the great deficiency of work on Arabic ontology development and the availability within the research team of an LMF standardized Arabic dictionary.
Abstract: The present paper proposes a methodology for generating core domain ontology from LMF standardized dictionary (ISO-24613). It consists in deriving the ontological entities systematically from the explicit information, taking advantage of the LMF dictionary structure. Indeed, such finely-structured source incorporates multi-domain lexical knowledge of morphological, syntactic and semantic levels, lending itself to ontological interpretations. The basic feature of the proposed methodology lies in the proper building of ontologies. To this end, we have integrated a validation stage into the suggested process in order to maintain the coherence of the resulting formalized ontology core during this process. Furthermore, this methodology has been implemented in a rule-based system, whose high-performance is shown through an experiment carried out on the Arabic language. This choice is explained not only by the great deficiency of work on Arabic ontology building, but also by the availability within our research team of an LMF standardized Arabic dictionary.
