Research on Data Deduplication of Power Material Supply Chain Based on Feature Iteration
The existing data deduplication methods of power material supply chain all have the situation of incomplete deduplica-tion or deletion of normal data.In order to strengthen the efficiency of data deduplication and effectively improve the perform-ance of deduplication,a method of data deduplication of power material supply chain based on feature iteration is proposed.This method carries out feature extraction and feature classification preprocessing on the power material supply chain data with the help of feature iteration,simplifies the amount of data in advance,reduces the difficulty of deduplication and the amount of calculation,and calculates the difference between the preprocessed data.With the help of the counting bloom filter algorithm,the similarity data that conforms to the deletion operation is calculated and deleted,so as to realize the data deduplication in the power supply chain.The experimental results show that the proposed method has the advantages of small storage space usage,good deduplication ability and short data deduplication time.
万方数据
维普
