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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How Multi-view Techniques Can Help in Processing Uncertainty, can be used in processing uncertainty—where many problems can reduced to a similar task of reconstructing properties of a multi-D object from its 1-D projections. In this chapter, we provide an overview of these techniques on the examples of probabilistic, interval, and fuzzy uncertainty, and of co

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Multi-view Clustering and Multi-view Models,iew data on a large scale. Multi-view data, in general, is large, heterogeneous and uncertain, but also contains a lot of knowledge to mine and apply. Some of the single-view data clustering techniques have been improved to analyze multi-view data by extending the structure of the objective function

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Data Anonymization Through Multi-modular Clustering,nes by opening their data. Anonymization of data refers to the process of removing sensitive data’s identifiers while keeping their structure and also the information type [.]. A fundamental challenge with data anonymization?is achieving a balance between the data’s worth and the degree of disclosur

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Conflagration

A Graph-Based Multi-view Clustering Approach for Continuous Pattern Mining,mponent of data streams. These models and algorithms also ought to take into account the multi-source nature of the sensor data by being able to conduct multi-view analysis. In this study, we address these challenges by introducing a novel multi-view data stream?clustering approach, entitled MST-MVS

Etching

Learning Shared and Discriminative Information from Multiview Data, dramatically. Huge amounts of data that abound with heterogeneous features representing distinct perspectives of the same underlying patterns arise in various scientific fields. For instance, LIDAR signals, radar signals, and camera videos can be seen as three different views of a particular self-d

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A Supervised Ensemble Subspace Learning Model Based on Multi-view Feature Fusion Employing Multi-telti-modalities or large sets of single modality data and extracts low order comprehensive attributes that effectively represents inherent characteristics of multiple sets sensor measurement associated with given physiological phenomena. This paper presents a multi-view feature fusion?based model tha

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