Aspects of automatic ontology extension: adapting and regeneralizing dynamic updates
Ekaterina Ovchinnikova, Kai‐Uwe Kühnberger · 2006
Ontologies are widely used in text technology and artificial intelligence. The need to develop large ontologies for real-life applications provokes researchers to automatize ontology extension procedures. Automatic updates without the control of a human expert can generate potential conflicts between original and new knowledge. As a consequence the resulting ontology can contain inconsistencies. On the other hand, even if the information extracted from the external sources automatically is consistent with the original ontology it can be generalized unsystematically and conceptually wrong. This in turn can lead to mistakes in applications of the extended ontology. We propose an algorithm that models the process of the adaptation of an ontology to new information and regeneralizes the resulting ontology in a more intuitive way inserting additional knowledge where this is possible.