Uncertain Schema Matching Based on Fuzzy Decision Making

Schema matching is very important in many database applications. Due to the semantic heterogeneity of data schemas, schema matching process contains uncertainty inherently. In order to manage uncertainty of schema matching, fuzzy decision making theory is employed to model schema matching process. The similarities of schema element pair given by independent matchers are aggregated to a triangular fuzzy number. Based on the priorities of these triangular fuzzy similarities an integrated strategy is proposed to select candidate mappings. The overall quality of our uncertain schema matching algorithm is verified by experiments.