Improved fuzzy comprehensive evaluation model of business website

In view of complexity of the business websites and fuzziness of quality evaluation, AHP-based multi-level fuzzy comprehensive evaluation become the advantage model for business website assessment. The core computing of Fuzzy Evaluation is the membership conversion, however, membership conversion way at present has a problem of redundancy, that is, the redundant data which has no value to objective classification in memberships of indicators is used to calculate the objective membership. In oder to obtain the membership conversion method which isn´t affected by interference of redundant data, we use entropy-based data mining method and define the distinguished weight through mining the knowledge information of objective classification hidden in membership of indicators. In this way, we abstract the effective value by mining the redundancy. Then we can calculate the membership of the objective by comparable value which get from the effective value. Thus, we construct a improved fuzzy comprehensive evaluation model of business website.