Research And Improvement Of Multi-Factor Correlation Analysis Algorithm For Government Procurement Data

Due to the acceleration of the negotiation process of my country's accession to GPA(Government Procurement Agreement)and the continuous deepening of government procurement reform,the scale of government procurement has gradually increased[1].Government procurement also plays an increasingly important role in economic development.Government procurement data contains information of a certain value.This article uses the association rule algorithm to process government procurement data,find out the strong correlation between the government procurement data elements,and provide a reference for the government procurement work to fight corruption and promote clean government.As government procurement generates more and more government procurement data,traditional data mining methods are powerless to analyze large amounts of data.Using big data and data mining methods to process government procurement data is the goal of this paper.In order to improve the efficiency of the original Apriori algorithm in processing large amounts of data and use the Apriori algorithm to analyze government procurement data,a Hadoop platform is adopted to improve the efficiency of the Apriori algorithm in processing data.The article describes in detail the Apriori algorithm,Hadoop-based h-Apriori and improved mh-Apriori algorithm,and implements these three algorithms,using data sets to verify the efficiency of the algorithm.The experiment of the paper is divided into three groups.The first group and the second group of experimental results show that the data sets chess and mushroom are processed by three algorithms,and the algorithm based on the Hadoop platform takes slightly longer than the original Apriori algorithm.The data set is not large,and Hadoop has no advantage in processing small amounts of data.The third set of experimental results shows that the two algorithms based on Hadoop are significantly better than the original Apriori algorithm in processing the accidents data set,and the mh-Apriori data processing efficiency is better than the h-Apriori algorithm.The visualization knowledge of association rules is elaborated,and the strong association relationship obtained by using the VOCAR method is displayed,and the association relationship between various elements is more clearly displayed,which provides a reference for the anti-corruption and advocacy of government procurement.