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Multi-View Multiple Clustering [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Multiple clustering aims at exploring alternative clusterings to organize the data into meaningful groups from different perspectives. Existing multiple clustering algorithms are designed for single-view data. We assume that the individuality and commonality of multi-view data can be leveraged to generate high-quality and diverse clusterings.
Shixin Yao +4 more
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Interpretable multi-view clustering [PDF]
Pattern RecognitionMulti-view clustering has become a significant area of research, with numerous methods proposed over the past decades to enhance clustering accuracy. However, in many real-world applications, it is crucial to demonstrate a clear decision-making process-specifically, explaining why samples are assigned to particular clusters. Consequently, there remains
Mudi Jiang +3 more
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From Ensemble Clustering to Multi-View Clustering [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Multi-View Clustering (MVC) aims to find the cluster structure shared by multiple views of a particular dataset. Existing MVC methods mainly integrate the raw data from different views, while ignoring the high-level information. Thus, their performance may degrade due to the conflict between heterogeneous features and the noises existing in each ...
Zhiqiang Tao +4 more
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One-step Multi-view Clustering Based on Diversity and Consistency [PDF]
Jisuanji gongchengWith the development of data collection technology, multi-view data have become increasingly common. Compared to single-view data, multi-view data contain richer information, which is usually characterized by consistency and diversity information.
HU Aoran, CHEN Xiaohong
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CMDC:an iterative algorithm for complementary multi-view document clustering [PDF]
Tongxin xuebao, 2020 In response to the problems traditional multi-view document clustering methods separate the multi-view document representation from the clustering process and ignore the complementary characteristics of multi-view document clustering,an iterative ...
Ruizhang HUANG +5 more
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, 2018 With a plethora of data capturing modalities becoming available, the same data object often leaves different kinds of digital footprints. This naturally leads to datasets comprising the same set of data objects represented in different forms, called multi-view data.
Padmanabhan, Deepak +1 more
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Multi-View MERA Subspace Clustering [PDF]
IEEE Transactions on Multimedia, 2023 Tensor-based multi-view subspace clustering (MSC) can capture high-order correlation in the self-representation tensor. Current tensor decompositions for MSC suffer from highly unbalanced unfolding matrices or rotation sensitivity, failing to fully explore inter/intra-view information. Using the advanced tensor network, namely, multi-scale entanglement
Zhen Long +5 more
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Contrastive and attentive graph learning for multi-view clustering [PDF]
, 2022 Graph-based multi-view clustering aims to take advantage of multiple view graph information to provide clustering solutions. The consistency constraint of multiple views is the key of multi-view graph clustering.
Li, Lin +4 more
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Trio-based collaborative multi-view graph clustering with multiple constraints [PDF]
, 2021 Multi-view graph clustering is an attentional research topic in recent years due to its wide applications. According to recent surveys, most existing works focus on incorporating comprehensive information among multiple views to achieve the clustering ...
Li, Lin +5 more
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A Graph-based Multi-view Clustering Approach for Continuous Pattern Mining [PDF]
, 2022 Today’s smart monitoring applications need machine learning models and data mining algorithms that are capable of analysing and mining the temporal component of data streams.
Devagiri, Vishnu Manasa, +2 more
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