Research on The Construction of Corruption Early Warning Mining Model Based on Big Data

Abstract

In the early warning information provided by the low-cost early warning model, due to the lack of a perfect low-cost index system, it is impossible to grade the early warning information and build a low-cost early warning mining model based on big data. First of all, a perfect integrity index system is constructed, and the index weight is selected by ratio scale method and Delphi method. Given the calculation method and evaluation index of low-cost index, the concept database and logic database of the model are designed to ensure information security. With the introduction of ¡strap data mining algorithm, and without changing the clustering results, combined with the low-cost index system to complete the level evaluation, on this basis, improve the warning function sequence diagram, so far completed the construction of warning mining model. In order to verify the effectiveness of the model, a comparative experiment is designed. The experimental results show that the designed early warning model, after big data mining, relies on the established low-cost index system to quantify the low-cost risk, so as to complete the evaluation of the risk level, which is consistent with the experimental settings, and that the designed model can effectively complete the evaluation of the early-warning risk level.