Mining method of college students'employment guidance resources based on data mining
When the current method is used for data mining of college students'employment guidance re-sources,due to the poor denoising performance,the method has the problems of data redundancy,low min-ing efficiency and poor accuracy.Therefore,a method based on data mining for college students'employ-ment guidance resources is proposed.H-BIRCH algorithm is used to cluster the employment guidance data,combined with EMD decomposition method and wavelet denoising method to de-noise different types of em-ployment information data,and whiten the denoised resource data.The graph model is used to extract the data features of employment guidance resources and complete the employment guidance resource mining.Experiment results show that the proposed method can effectively simplify the data structure,and has high data redundancy error correction rate,data mining efficiency and data mining accuracy.
万方数据
维普
