自动化学报2024，Vol.50Issue(6)：1160-1170,11.DOI:10.16383/j.aas.c220531
基于加权锚点的多视图聚类算法
Multi-view Clustering With Weighted Anchors
摘要
Abstract
Large-scale multi-view clustering aims to solve the problem that traditional methods cannot scale to large-scale data due to slow computational speed and high complexity.Among them,the anchor-based multi-view clustering method constructs a reconstruction matrix for the entire dataset by utilizing a set of anchor points.Clus-tering with the reconstruction matrix effectively reduces the time and space complexity of the algorithm.However,existing methods ignore the differences among anchor points and treat them equally,resulting in clustering results limited by low-quality anchor points.In order to identify more discriminative anchor points and enhance the influ-ence of high-quality anchors on clustering,a large-scale multi-view clustering algorithm based on weighted anchors(MVC-WA)was proposed.By introducing an adaptive anchor weighting mechanism,the proposed method determ-ine the weights of anchors in a unified framework for the construction of anchor graphs.Meanwhile,in order to in-crease the diversity among anchors,the weights of anchors were further adjusted according to the similarity between them.Experimental results comparing with existing state-of-the-art large-scale multi-view clustering al-gorithms on nine benchmark datasets validate the efficiency and effectiveness of the proposed method.关键词
多视图聚类/大规模聚类/锚点/权重学习Key words
Multi-view clustering/large-scale clustering/anchor/weight learning引用本文复制引用
刘溯源,王思为,唐厂,周思航,王思齐,刘新旺..基于加权锚点的多视图聚类算法[J].自动化学报,2024,50(6):1160-1170,11.基金项目
国家自然科学基金(61922088,62006236,62006237),国防科技大学科研计划项目(ZK21-23,ZK20-10),高性能计算国家重点实验室自主课题(202101-15)资助 Supported by National Natural Science Foundation of China(61922088,62006236,62006237),Research Project of National University of Defense Technology(ZK21-23,ZK20-10),and Autonomous Project of State Key Laboratory of High Perform-ance Computing(202101-15) （61922088,62006236,62006237）
