Abstract: In order to take into account the effect of relaxation function dependency detection and reduce the computational complexity, a data quality detection based on multi-attribute dominance and relaxation function dependency is proposed. A data quality detection algorithm for relaxed functional dependencies was proposed. The algorithm could automatically infer the similarity threshold by expressing the distance between multiple attribute values as an index through the advantage concept in multiple attribute decision-making theory. A utility function was introduced, which could be sorted according to the cardinality and threshold of the relaxation function. The experimental evaluation on the real data set shows that the proposed method has high detection accuracy and low computational complexity.