Affected by the unbalanced distribution of grid storage space

resulting in large data mining cluster registration is not high

in order to improve the efficiency of data mining

proposes an improved algorithm for mining large data association based on fuzzy partition clustering analysis. The grid structure model in the cloud storage space in the data association

semantic rules of feature extraction big data flow of information

the feature extraction of adaptive weighted attribute data processing

enhance the intensity distribution

the extracted data association features optimized clustering using fuzzy partition method in the storage space

the semantic partition based on clustering results

construct discriminant statistics and test criteria for data mining clustering attribute judgment to improve the accuracy of data mining

data mining optimization. The simulation results show that using the method of performance data mining area Better

the accuracy of data classification is higher

and the accuracy of data is improved.