This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling ...
Instance-based ontology mapping comprises a collection of theoretical approaches and applications for identifying the implicit semantic similarities between two ontologies on the ...
For their usage in the semantic web, valid ontologies are required for a given domain. Here we focus on ontologies represented as concept maps (semantic nets). For one and the sam...
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...
The difficulty of domain knowledge acquisition is one of the most sensible challenges of intelligent tutoring systems. Relying on domain experts and building domain models from sc...