Similarity Measurement for Retrieval Based on Hybrid Attribute Distance

Abstract:

A new similarity measure method based on hybrid attribute distance was introduced. Overall distance between two cases was determined by distances between attributes and synthesis weights. First, a degree of similarity was characterized by overall distance. Based on the distance formula of interval numbers and the theory of fuzzy set, a distance formula of fuzzy numbers and fuzzy interval numbers was given and the distance formula of membership function was improved. Meanwhile, the deviation information of distance values was used to calculate objective weights regarding weights assignment, then objective weights and subjective weights were integrated into synthesis weights to calculate the overall similarity of the cases. Lastly, the method was applied to the conceptual design of valve. The effectiveness and feasibility of the method in case retrieval were demonstrated.