Huge amounts of telecom data are generated every day

so how to extract useful information from the data is one of the data mining problems. Because different applications need different clusters

sometimes a single K-means cluster algorithm cannot generate userspecified K-clusters. An adjustable multitimes clustering mining method is proposed. A big value K was used in the K-means clustering algorithm for the first time

and K clusters were obtained. They were used to select the number of the clusters and the initial centers of the clusters for the second time. The experimental results show that our method is effective

and it can be applied to mining different amounts of clusters and big data analysis.