Abstract: A novel generalized quantum particle model (GQPM) was presented for data self-organizing clustering. In this model the data clustering process is transformed into a stochastic self-organizing process of the ctuantum particles in the state configuration space. I}he state configuration will evolve to a stationary probability distribution, and thus the optimal state configuration on particles can be obtained from the state configuration which has the highest probability in the stationary probability distribution. The convergence of the self-organizing process was proved in this paper. The GQPM algorithm has much faster clustering speed than the traditional clustering algorithm for the large scale database.Its superiorities were verified by the simulation experiments.

Key words: Data clustering, Multidimensional data, Stochastic process, Markov chain