NLP AND ONTOLOGY MATCHING A Successful Combination for Trialogical Learning

Trialogical Learning refers to those forms of learning where learners are collaboratively developing, transforming, or creating shared objects of activity in a systematic fashion. In order to be really productive, systems supporting Trialogical Learning must rely on intelligent services to let knowledge co-evolve with social practices, in an automatic or semi-automatic way, according to the users' emerging needs and practical innovations. These requirements raise problems related to knowledge evolution, content retrieval and classification, dynamic suggestion of relationships among knowledge objects. In this paper, we propose to exploit Natural Language Processing and Ontology Matching techniques for facing the problems above. The Knowledge Practice Environment of the KP-Lab project has been used as a test bed for demonstrating the feasibility of our approach.