计算机应用研究2024，Vol.41Issue(1)：102-107,115,7.DOI:10.19734/j.issn.1001-3695.2023.05.0195
基于相似图投影学习的多视图聚类
Multi-view clustering based on similarity graph projection learning
摘要
Abstract
With the diversified development of data sources,multi-view clustering has become a research hotspot.Most algo-rithms focus too much on using graph structure to seek consistent representation,but ignore how to learn the graph structure it-self.In addition,some methods are usually optimized based on fixed views.In order to solve these problems,this paper pro-posed a multi-view clustering algorithm based on similarity graph projection learning(MCSGP),which effectively fused the global structure information and local potential information into a consensus graph by using the projection graph,rather than only pursuing the consistency of each view with the consensus graph.By imposing a rank constraint on the graph Laplacian ma-trix of the consensus graph matrix,this algorithm could naturally divide the data points into the required number of clusters.In the experiments on two artificial datasets and seven real datasets,the MCSGP algorithm shows excellent clustering effect on ar-tificial data sets.At the same time,in the real datasets involving 21 indicators,17 indicators reach the optimal level,which fully proves the superior performance of the proposed algorithm.关键词
多视图聚类/投影学习/相似图/图融合Key words
multi-view clustering/projection learning/similarity graph/graph fusion分类
信息技术与安全科学引用本文复制引用
赵伟豪,林浩申,曹传杰,杨晓君..基于相似图投影学习的多视图聚类[J].计算机应用研究,2024,41(1):102-107,115,7.基金项目
广东省面上自然科学基金资助项目(2021A1515011141) （2021A1515011141）
国防重点实验室开放基金资助项目 （）
国家自然科学基金青年资助项目(61904041) （61904041）
