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Title: | A Survey and an Empirical Evaluation of Multi-view Clustering Approaches |
Authors: | Zhou, L Du, G Lü, K Wang, L Du, J |
Keywords: | multi-view clustering;consensus and complementary principles;information fusion;weighting;clustering routine |
Issue Date: | 1-Apr-2024 |
Publisher: | Association for Computing Machinery (ACM) |
Citation: | 10.1145/3645108, L. et al. (2024) 'A Survey and an Empirical Evaluation of Multi-view Clustering Approaches', ACM Computing Surveys, 56 (`7), pp. 1 - 38. doi: 10.1145/3645108. |
Abstract: | Multi-view clustering (MVC) holds a significant role in domains like machine learning, data mining, and pattern recognition. Despite the development of numerous new MVC approaches employing various techniques, there remains a gap in comprehensive studies evaluating the characteristics and performance of these approaches. This gap hinders the in-depth understanding and rational utilization of the recently developed MVC techniques. This study formalizes the basic concepts of MVC and analyzes their techniques. It then introduces a novel taxonomy for MVC approaches and presents the working mechanisms and characteristics of representative MVC approaches developed in recent years. Moreover, it summarizes representative datasets and performance metrics commonly employed for evaluating MVC approaches. Furthermore, we have meticulously chosen 35 representative MVC approaches to conduct an empirical evaluation across seven real-world benchmark datasets, offering valuable insights into the realm of MVC approaches. |
Description: | Supplementary Material is available online at: https://dl.acm.org/doi/10.1145/3645108#supplementary-materials . Code is availailable online at: https://github.com/dugzzuli/A-Survey-of-Multi-view-Clustering-Approaches . |
URI: | https://bura.brunel.ac.uk/handle/2438/30220 |
DOI: | https://doi.org/10.1145/3645108 |
ISSN: | 0360-0300 |
Other Identifiers: | ORCiD: Lihua 10.1145/3645108 https://orcid.org/0000-0002-8940-1155 ORCiD: Guowang Du https://orcid.org/0000-0002-8109-7152 ORCiD: Kevin Lü https://orcid.org/0000-0002-2588-9059 ORCiD: Lizheng Wang https://orcid.org/0000-0003-2214-2299 ORCiD: Jingwei Du https://orcid.org/0009-0001-6774-1685 187 |
Appears in Collections: | Brunel Business School Research Papers |
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FullText.pdf | Copyright © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Computing Surveys, https://doi.org/10.1145/3645108 (see: https://www.acm.org/publications/policies/copyright-policy). | 1.29 MB | Adobe PDF | View/Open |
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