“…Multi-view clustering aims to utilize the features of multiple views to achieve a unified clustering result. In recent years, many multi-view clustering methods have been designed from different technical perspectives [2,3,5,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28]. Some important categories in multi-view clustering include the co-training based methods [13,14,15], the multi-kernel based methods [16,17,19,20], the graph learning based methods [23,24,25,26], and the subspace learning based methods [2,3,5].…”