In-depth Data Mining Method of Network Shared Resources Based on K-means Clustering

In order to improve the accuracy and efficiency of in-depth data mining of network shared resources, a new method of in-depth data mining of network shared resources based on K-means clustering is designed. The advantages of K-means clustering algorithm are analyzed, and the clustering processing of network shared resource data is carried out by K-means clustering algorithm, and the data feature vectors in the clustering results are extracted. Based on the data feature vector extraction results, a deep mining model of network shared resource data is built, and the model is solved, and the results of deep mining of network shared resource data are output. Experimental results show that this method can achieve accurate and fast network shared resource data deep mining, practical application effect is better.