The Effective Genetic Clustering Algorithm and The Optimization of The Web Advertising Investment

To the problem that it is hard to determine the clustering number and the abnormal points by using the clustering validity function, an effective clustering partition model based on the genetic algorithm is built in this paper. The solution to the problem is formed by the combination of the clustering partition and the encoding samples, and the fitness function is defined by the distances among and within clusters. The clustering number and the samples in each cluster are determined and the abnormal points are distinguished by implementing the triple random crossover operator and the mutation. The optimization of the Web advertising investment is turned into the problem of the partition of the quality of the Web advertising keywords. The best clustering number and the clustering result of the Web advertising keyword are obtained by applying the effective genetic clustering algorithm for the partition of the keyword and then the investment decision is determined