A SYSTEMIC METHODOLOGY FOR ONTOLOGY LEARNING An Academic Case Study and Evaluation

There is an important dispersion of technical and methodological resources to support the complete Ontology Learning (OL) process from diverse knowledge sources. This fact makes the maintaining of the structures of representation (ontologies) difficult. Therefore, the Knowledge-based Systems associated with user's domains may not fulfil the increasing knowledge requirement from the user. In this paper, we give a possible solution for this problem. For this purpose, we propose a Systemic Methodology for OL (SMOL) that unifies and simplifies to the users the whole process of OL from different knowledge sources (ontologies, texts and databases). SMOL as methodology is evaluated under DESMET methods, in addition with their application for an academic case study is also included.