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as the network data today is massive, so the researchers on the study of some problems need to be different from the properties of the data extraction, however, these data will be required clustering before extracting the same data . The process of data clustering is the process of finding the optimal attributes of data. However, the artificial ant colony is an algorithm for finding the optimal solution of the problem. Therefore, the ant colony algorithm is applied to the clustering in this paper. The clustering algorithm proposed by this paper can be divided into two parts, the first part is: through the similarity algorithm to measure the similarity between the data, the second part is: according to the results of the first part, using ant colony algorithm to select different clustering in the heart for clustering data, and clustering of the different attributes of the data. Through the calculation of the above two processes, can realize the clustering of data. In this paper, the similarity measure used in data clustering is used to replace the distance calculation. It is one of the innovations of this paper. It is also the innovation of this paper that the ant colony algorithm is used to select the cluster center in the clustering process.