An active learning algorithm based on pair-wise constraints with error correction is proposed in this paper. The
algorithm searches the pair-wise constraints information that the clustering algorithm cann’t find, and tries its best to reduce
the connections between these constraint informations, which is used in the spectral clustering. The suppervised information
is used to adjust the distance matrix in the spectral clustering, and the distances are sorted. The learninger can study actively
when the learinger receives the data without flags by using the two-way search method. Experiment analysis shows that
better clustering result can be obtained by using the proposed method.