Summary: A binary quantum-behaved particle swarm optimization (BQPSO) algorithm based on a comprehensive learning strategy is proposed in order to improve convergence. Then, a new data clustering method is designed according to comprehensive learning BQPSO (CLBQPSO). The new clustering algorithm is compared with some other clustering algorithms on four test datasets. The experimental results show that the CLBQPSO clustering algorithm not only converges faster but also has the better global convergence.