A Formal Foundation For Knowledge Integration Of Defficent Information In The Semantic Web

Maintenance of logical robustness in Information Integration represents a major challenge in the envisioned Semantic Web. In this framework, it is previsible unprecise information (with respect to an ontology) is retrieved from some resources. The sound integration of such information is crucial to achieve logical soundness. We present a data-driven approach to classify that knowledge by means of the cognitive entropy of the possible robust ontology extensions and data.