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Multi-view clustering via global-view graph learning. [PDF]
PLoS ONEMultiview clustering aims to improve clustering performance by exploring multiple representations of data and has become an important research direction. Meanwhile, graph-based methods have been extensively studied and have shown promising performance in
Qin Li, Geng Yang
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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]
EntropyMulti-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 +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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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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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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Tsinghua Science and Technology, 2021 In recent years, multi-view clustering research has attracted considerable attention because of the rapidly growing demand for unsupervised analysis of multi-view data in practical applications.
Jie Hu, Yi Pan, Tianrui Li, Yan Yang
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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 +4 more
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Multi-View Fuzzy Clustering Algorithm Fused with KL Information [PDF]
Jisuanji gongcheng, 2022 Existing multi-view Fuzzy C-Means(FCM) clustering algorithms usually artificially decompose multi-view data into multiple single-view data for processing, reducing the clustering accuracy of view data and affecting the results of global data division.To ...
HE Na, MA Yingcang
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