Social Network Big Data Hierarchical High-Quality Node Mining

Algorithm 1

Input: the dataset with samples and the number of clusters .

Output: clusters and minimizes the squared error criterion.

Steps.

(1) Arbitrarily select samples as initial cluster centers

(2) Repeat the above steps

(3) Calculate the mean of the samples in the cluster and reassign the values of the samples to the most similar cluster

(4) Updating the cluster means, i.e., calculating the mean of the samples in each cluster

(5) Until no more changes occur