Ontology-Driven Method for Ranking Unexpected Rules
نویسندگان
چکیده
Several rule discovery algorithms have the disadvantage to discover too much patterns sometimes obvious, useless or not very interesting to the user. In this paper we propose a new approach for patterns ranking according to their unexpectedness using semantic distance calculated based on a prior background knowledge represented by domain ontology organized as DAG (Directed Acyclic Graph) hierarchy.
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