Studying and analyzing on data streams mining technique based on clustering method

With the development of data gathering and communication technologies,it becomes increasingly possible to support real-time monitoring of large amount of information from diverse information sources.A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate.Due to this reason,traditional data mining approach is replaced by the system that is able to mine continuous,high-volume,open-ended data streams as they arrive.This paper introduces a new algorithm using clustering method to improve the data streams mining technique.We have studied clustering data streams using K-Means algorithm,statistical grid-based algorithm and regression analysis and compared these techniques.