Titlebook: Recent Advancements in Multi-View Data Analytics; Witold Pedrycz,Shyi-Ming Chen Book 2022 The Editor(s) (if applicable) and The Author(s),

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Rethinking Collaborative Clustering: A Practical and Theoretical Study Within the Realm of Multi-ving and unsupervised ensemble learning. We do so by addressing both practical and theoretical aspects: First we address the formal definition of what is collaborative clustering as well as its practical applications. By doing so, we demonstrate that pretty much everything called collaborative cluster

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An Optimal Transport Framework for Collaborative Multi-view Clustering,er we propose two approaches: Collaborative Consensus Projection Approach (CoCP) that aims to perform the consensus in the global space of the data, and a Collaborative Consensus with New Representation (CoCNR) that seeks to encode a new data representation based on local ones. Both approaches are b

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Data Anonymization Through Multi-modular Clustering,sion does it through exploration. Additionally, we boosted the performance of these two strategies by including the pLVQ2 weighted vector quantization method. These techniques were evaluated on the basis of two metrics: separability and structural utility. The obtained experimental results indicate

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A Graph-Based Multi-view Clustering Approach for Continuous Pattern Mining,l nodes used by the MST clustering algorithm. These artificial nodes are identified by analyzing multi-view patterns extracted at each data chunk in the form of an integrated (global) clustering model. We further show how the extracted patterns can be used for post-labelling of the chunk’s data by i

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