Affinity propagation (AP) algorithm takes all data as potential clustering centers. Clustering is carried out by message passing based on the similarity matrix. But it is not appropriate for subspace clustering. AP subspace clustering algorithm based on attributes relation matrix (ARMAP) is an asynchronous soft subspace clustering algorithm. This algorithm calculates attribute relation matrix through α-β neighborhood of attribute a. The candidate of all interesting subspaces is achieved by looking for the maximum sub-matrixes of attribute relation matrix which contain only 1. All subspace clusters can be obtained through AP clustering on interesting subspaces. The method obtains interesting subspaces correctly and reduces time complexity at the same time. It not only keeps the advantages of AP clustering algorithm, but also overcomes the shortcomings of AP algorithm which can not be used for subspace clustering.