AN EMPIRICAL RESEARCH OF DYNAMIC CLUSTERING ALGORITHMS

ABSTRACT Clustering and visualizing high dimensional dynamic data is a challenging problem in the data mining. Most of the existing clustering algorithms are based on the static statistical relationship among data. In the clustering process there are no predefined classes and no examples that would show what kind of desirable relations should be valid among the data. This paper gives existing work done in some papers related with dynamic clustering and incremental data clustering. Since most researchers will move and concentrate on solving the problem of using data mining dynamic databases