Data Stream Clustering Algorithm Based on Density and Fractal Dimension

Considering deficiencies of some popular data stream clustering algorithms,a data stream clustering algorithm based on density and fractal dimension is presented.It consists of two phases of online and offline processing,combined with the advantages of density clustering and fractal clustering.The deficiency of the traditional clustering algorithm is overcome.In the algorithm,a density decaying strategy to reflect the timelines of data stream is adopted.Experimental results show the algorithm improves the efficiency and accuracy of data stream clustering,and can find arbitrary shapes and non-neighboring clusters.