Web data mining algorithm based on cloud computing environment

The purpose of this article is to study web data mining algorithms in the cloud. In order to quickly extract valuable rules and patterns from massive and noisy data, and make them easy to understand and directly apply, we use data mining technology. On the other hand, based on the low cost of cloud computing, large throughput, good fault tolerance, and strong stability, the web chose the cloud computing method. This paper studies and analyses the K-Means clustering algorithm, and uses the web data mining algorithm based on the cloud computing environment to improve the K-Means algorithm, overcomes the shortcomings of the K-Means algorithm itself, and builds a good cloud computing environment. The research results show that the improved and optimised algorithm in this paper solves the problem of insufficient speed and efficiency in the clustering process.