Classification of contradiction patterns

Abstract

Solving conflicts between overlapping databases requires an understanding of the reasons that lead to the inconsistencies. Provided that conflicts do not occur randomly but follow certain regularities, patterns in the form of "If condition Then conflict" provide a valuable means to facilitate their understanding. In previous work, we adopt existing association rule mining algorithms to identify such patterns. Within this paper we discuss extensions to our initial approach aimed at identifying possible update operations that caused the conflicts between the databases. This is done by restricting the items used for pattern mining. We further propose a classification of patterns based on mappings between the contradicting values to represent special cases of conflict generating updates.