{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T13:25:41Z","timestamp":1770816341467,"version":"3.50.1"},"reference-count":0,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,5,29]],"date-time":"2024-05-29T00:00:00Z","timestamp":1716940800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62276164"],"award-info":[{"award-number":["62276164"]}]},{"name":"National Natural Science Foundation of China","award":["61602296"],"award-info":[{"award-number":["61602296"]}]},{"name":"National Natural Science Foundation of China","award":["22ZR1427000"],"award-info":[{"award-number":["22ZR1427000"]}]},{"name":"Natural Science Foundation of Shanghai","award":["62276164"],"award-info":[{"award-number":["62276164"]}]},{"name":"Natural Science Foundation of Shanghai","award":["61602296"],"award-info":[{"award-number":["61602296"]}]},{"name":"Natural Science Foundation of Shanghai","award":["22ZR1427000"],"award-info":[{"award-number":["22ZR1427000"]}]},{"name":"Shanghai Oriental Talent Program-Youth Program","award":["62276164"],"award-info":[{"award-number":["62276164"]}]},{"name":"Shanghai Oriental Talent Program-Youth Program","award":["61602296"],"award-info":[{"award-number":["61602296"]}]},{"name":"Shanghai Oriental Talent Program-Youth Program","award":["22ZR1427000"],"award-info":[{"award-number":["22ZR1427000"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Multi-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, existing deep multi-view clustering methods often focus only on either consistency information or diversity information, making it difficult to balance both aspects. Therefore, this paper proposes a view-driven multi-view clustering using the contrastive double-learning method (VMC-CD), aiming to generate better clustering results. This method first adopts a view-driven approach to consider information from other views to encourage diversity, thus guiding feature learning. Additionally, it presents the idea of dual contrastive learning to enhance the alignment of views at both the clustering and feature levels. The VMC-CD method\u2019s superiority over various cutting-edge methods is substantiated by experimental findings across three datasets, affirming its effectiveness.<\/jats:p>","DOI":"10.3390\/e26060470","type":"journal-article","created":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T08:15:54Z","timestamp":1717056954000},"page":"470","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["View-Driven Multi-View Clustering via Contrastive Double-Learning"],"prefix":"10.3390","volume":"26","author":[{"given":"Shengcheng","family":"Liu","sequence":"first","affiliation":[{"name":"Information Engineering College, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changming","family":"Zhu","sequence":"additional","affiliation":[{"name":"Information Engineering College, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zishi","family":"Li","sequence":"additional","affiliation":[{"name":"Information Engineering College, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyuan","family":"Yang","sequence":"additional","affiliation":[{"name":"Information Engineering College, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjie","family":"Gu","sequence":"additional","affiliation":[{"name":"Information Engineering College, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,29]]},"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/26\/6\/470\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:50:25Z","timestamp":1760107825000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/26\/6\/470"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,29]]},"references-count":0,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["e26060470"],"URL":"https:\/\/doi.org\/10.3390\/e26060470","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,29]]}}}