Fuzzy Comprehensive Evaluation on Digital Libraries Based on Membership Degree Transformation New Algorithm-M(1,2,3)

Abstract

In the evaluation process of digital libraries, there are many aspects needing to consider, with a lot of uncertainty and ambiguity, so it is reasonable and scientific to apply fuzzy comprehensive evaluation method for digital library fuzzy evaluation. The core of fuzzy evaluation is membership degree transformation. But the existing transformation methods should be questioned, because redundant data in index membership degree is also used to compute object membership degree, which is not useful for object classification. The new algorithm is: using data mining technology based on entropy to mine knowledge information about object classification hidden in every index, affirm the relationship of object classification and index membership, eliminate the redundant data in index membership for object classification by defining distinguishable weight and extract valid values to compute object membership. The new algorithm of membership degree transformation includes three calculation steps which can be summarized as effective, comparison and composition, which is denoted as M(1,2,3). The paper applied the new algorithm in the fuzzy evaluation of digital libraries.