A Research Of Developed Algorithms About Text Cluster Center Choose

K-means clustering algorithm is a division based on the clustering algorithm, many clustering algorithm in the performance comparison, the algorithm is efficient, can be found clustering of arbitrary shape, the order of data input is not sensitive, and the high-dimensional data also have better performance, so it is used widely. But K-means algorithm need to specify K-value in advanced, and it is sensitive to the "noise" and isolating data points. This article developed a new algorithm over the shortcomings of the K-means algorithm. Firstly, samples collected and divided into subsets, serial clustering. Secondly, genetic algorithm will join the K-means algorithm, to select the center of the cluster. And experiments show that, this new algorithm is better not only in the precision of cluster result, but also in the accuracy of cluster center choosing than the traditional K-means algorithm.