Enterprise Precision Marketing Effectiveness Model Based on Data Mining Technology

Algorithm 3

Description of K-means clustering algorithm based on artificial bee colony.

(a)	Initialize the total number of samples is M, and the number of clusters is K.
(b)	Initialize source according to formula (2).
(c)	Based on the cluster center in step b), select a plan, and assign another M-K noncluster center sample to K clusters, so that the sum of the distances between each sample and the cluster center is minimized.
(d)	Use the K-means method to update the cluster center nodes. Calculate the fitness value of each source according to formula (1).
(e)	Follow the new source according to the artificial bee colony algorithm described in Section 3.2.