吉林大学学报（理学版）2025，Vol.63Issue(2)：537-550,14.DOI:10.13413/j.cnki.jdxblxb.2024077
基于一致性和差异性的低秩张量多视图聚类算法
Multi-view Clustering Algorithm with Low-Rank Tensor Based on Consistency and Difference
摘要
Abstract
Aiming at how to utilize the implicit information in multi-view data and avoid the problem of sub-optimal clustering performance in the subsequent processing,we proposed a multi-view clustering algorithm with low-rank tensor based on consistency and difference.Firstly,the algorithm simultaneously considered the consistency and differential information of views,and superimposed multiple consistent similarity matrices in a tensor constrainted by low-rank to explore the higher-order correlations of the information between views,thus obtaining higher-quality similarity matrices.Secondly,clustering results were directly obtained by learning a consistent non-negative embedding matrix.Thirdly,an adaptive weighting strategy was used to consider the importance of different view data.Finally,the effectiveness of the algorithm on the multi-view clustering problem was verified by comparison experiments with other algorithms on six real datasets.关键词
多视图聚类/一致性/差异性/低秩张量表示/自适应加权Key words
multi-view clustering/consistency/difference/low-rank tensor representation/adaptive weighting分类
信息技术与安全科学引用本文复制引用
周余琳,王长鹏..基于一致性和差异性的低秩张量多视图聚类算法[J].吉林大学学报（理学版）,2025,63(2):537-550,14.基金项目
国家自然科学基金(批准号:12471480)和长安大学中央高校基本科研业务费专项基金(批准号:300102122101). （批准号:12471480）
