Rapid Mining Algorithm for Low-dimensional Redundant Uunstructured Data Based on Rough Neural Network
In order to better optimize the mining efficiency,reduce the mining error and the mining response time,according to the characteristics of unstructured data,on the basis of rough set strategy,the rough neural network is used to optimize the mining process of low-dimensional redundant unstructured data.The unstructured data cleaning model is established based on rough neural network.Low-dimensional redundant unstructured data feature is extracted.Mining support quantity is calculated and outputted.The experimental results show that the mining effect optimized by the proposed method is excellent in terms of overall efficiency,response speed,and mining accuracy.It can meet the requirements of practical applications,and solve the problems of large error and low efficiency.