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Multi-view Clustering: A Survey

Big Data Mining and Analytics, 2018
In the big data era, the data are generated from different sources or observed from different views. These data are referred to as multi-view data. Unleashing the power of knowledge in multi-view data is very important in big data mining and analysis ...
Yan Yang, Hao Wang
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View-Driven Multi-View Clustering via Contrastive Double-Learning [PDF]

Entropy
Multi-view clustering requires simultaneous attention to both consistency and the diversity of information between views. Deep learning techniques have shown impressive abilities to learn complex features when working with extensive datasets; however ...
Shengcheng Liu, Changming Zhu, Zishi Li, Zhiyuan Yang, Wenjie Gu   +4 more
doaj   +2 more sources

Federated Multi-View Spectral Clustering

IEEE Access, 2020
Multi-view spectral clustering (MVSC) has become a popular approach to harvest knowledge about group information from multiple views of data, owned by different parties. A high quality MVSC approach usually requires collecting massive amount of data from
Hongtao Wang, Ang Li, Bolin Shen, Yuyan Sun, Hongmei Wang   +4 more
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Subtype identification from heterogeneous TCGA datasets on a genomic scale by multi-view clustering with enhanced consensus [PDF]

BMC Medical Genomics, 2017
Background The Cancer Genome Atlas (TCGA) has collected transcriptome, genome and epigenome information for over 20 cancers from thousands of patients. The availability of these diverse data types makes it necessary to combine these data to capture the ...
Menglan Cai, Limin Li
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Multi-View Kernel Spectral Clustering [PDF]

Information Fusion, 2018
Abstract In multi-view clustering, datasets are comprised of different representations of the data, or views. Although each view could individually be used, exploiting information from all views together could improve the cluster quality. In this paper a new model Multi-View Kernel Spectral Clustering (MVKSC) is proposed that performs clustering when
Lynn Houthuys, Rocco Langone, Johan A K Suykens   +2 more
exaly   +4 more sources

Multi-Task Multi-View Clustering

IEEE Transactions on Knowledge and Data Engineering, 2016
Multi-task clustering and multi-view clustering have severally found wide applications and received much attention in recent years. Nevertheless, there are many clustering problems that involve both multi-task clustering and multi-view clustering, i.e., the tasks are closely related and each task can be analyzed from multiple views.
Xiaotong Zhang, Xianchao Zhang
exaly   +2 more sources

Multi-view clustering via global-view graph learning [PDF]

PLoS ONE
Qin Li, Geng Yang
doaj   +2 more sources

Unsupervised Multi-View K-Means Clustering Algorithm

IEEE Access, 2023
Since advanced technologies via social media, internet, virtual communities and networks and internet of things (IoT), there are more multi-view data to be collected.
Miin-Shen Yang, Ishtiaq Hussain
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FMvC: Fast Multi-View Clustering

IEEE Access, 2023
In multi-view clustering, an eigen-decomposition of the Laplacian matrix of the graph is usually necessary. This leads to a significant increase in time cost and also requires post-processing such as $k$ -means.
Jiada Wang, Yijun Liu, Wujian Ye
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An improved multi-view spectral clustering based on tissue-like P systems

Scientific Reports, 2022
Multi-view spectral clustering is one of the multi-view clustering methods widely studied by numerous scholars. The first step of multi-view spectral clustering is to construct the similarity matrix of each view.
Huijian Chen, Xiyu Liu
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