Conceptual reinforcement in concept maps using computer inference

Abstract

The importance of a concept on a concept map is proportional to the amount of relationships in which it participates. By adding new relationships to a concept, we are highlighting it and reinforcing its role on the map, with several pedagogical applications. We use language processing techniques and rules for automatic inference from concept maps to identify and suggest new relationships on a map. This article presents a model for finding new relationships in concept maps; shows a software architecture that implements this model and reports some test cases and perspectives for future work.