Use of Ranking Data in Similar Set Retrieval Systems

Abstract

This paper discusses the problems of the similar set retrieval based on averaged error sums with different measures. Since the ranking data of two averaged error sums couldn't be combined for well-informed retrieval, the averaged error grades, which are obtained by normalizing the averaged error sums by the maximum, were employed to get the membership grade of the similar set by the difference to 1. The retrieval system has been designed to find the nearest set based on MIN operation and the ranking of the membership grades.