计算机工程与应用2025，Vol.61Issue(23)：135-148,14.DOI:10.3778/j.issn.1002-8331.2408-0004
融合一致性和多样性的自适应加权多视图聚类
Auto-Weighted Multi-View Clustering Incorporating Consensus and Diversity
摘要
Abstract
Multi-view clustering exhibits excellent clustering performance because it can fully integrate information from multiple views.However,most of the existing methods focus only on the consensus information among views,while ignoring the diversity information among views and lacking the accuracy of approximation rank,which ultimately affects the effectiveness of the clustering results.To handle this issue,a multi-view clustering algorithm based on the tensor log-determinant,named auto-weighted multi-view clustering incorporating consensus and diversity is proposed.Specifically,this algorithm first constructs an initial similarity graph for each view,and then uses the tensor log-determinant to maxi-mally approximate the true value of the rank.Subsequently,the algorithm explores intra-view and inter-view diversity in-formation by using a diversity term,and uses an adaptive weighted graph fusion term to extract consensus information from each view.Through iterative optimization,a high-quality fusion graph is finally obtained.Experimental results on eight real-world datasets show that the proposed method significantly outperforms state-of-the-art baselines.关键词
多视图聚类/一致性信息/多样性信息/自适应加权Key words
multi-view clustering/consensus information/diversity information/adaptive weighting分类
信息技术与安全科学引用本文复制引用
姚怡莹,陈梅,王洁,郭爱霞..融合一致性和多样性的自适应加权多视图聚类[J].计算机工程与应用,2025,61(23):135-148,14.基金项目
国家自然科学基金(62266029) （62266029）
甘肃省重点研发计划(24YFGA036) （24YFGA036）
甘肃省高等学校产业支撑计划(2022CYZC-36). （2022CYZC-36）
