Fuzzy Comprehensive Evaluation on Community Service Based on Improved Algorithm

With the development of community service work, community service evaluation becomes more and more important. However, there are not quantitative methods widely accepted for evaluating on community service. Therefore, evaluation on community service is often with a lot of arbitrary and subjective. Using data mining technology based on entropy to mine knowledge information about object classification hidden in every index, the paper affirmed the relationship of object classification and index membership and eliminated 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 fuzzy comprehensive evaluation on community service.