Zobrazeno 1 - 10
of 1 755
pro vyhledávání: '"multi-view clustering"'
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 11, Pp 3027-3040 (2024)
The multi-view clustering algorithm is a novel approach to explore the inherent clustering structure among data. However, most existing methods suffer from noise issues when constructing similarity graphs and may lose important information during the
Externí odkaz:
https://doaj.org/article/2d6485b807744f559dcf43ee883bbec8
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 10, Pp 2750-2761 (2024)
Multi-view clustering algorithm based on graph learning has been widely concerned in recent years because of its simplicity and high efficiency. Most of multi-view clustering algorithms only consider the consistent part of each view and ignore the di
Externí odkaz:
https://doaj.org/article/5cb2ad212c6a48dcae5b00d38c10c47d
Publikováno v:
Frontiers of Urban and Rural Planning, Vol 2, Iss 1, Pp 1-13 (2024)
Abstract With the booming of Big Data and the Internet of Things, various urban networks have been built based on intercity flow data, and how to combine them to learn a more comprehensive understanding of mega-city regions is becoming more and more
Externí odkaz:
https://doaj.org/article/b5984607aecb4a09a4029fab80cba0c1
Autor:
Yaosong Yu, Dongpu Sun
Publikováno v:
IEEE Access, Vol 12, Pp 19087-19099 (2024)
Aiming at the existing incomplete multi-view clustering methods that usually ignore the noise and redundancy of the original data, hide the valuable information in the missing views, and the different importance of each view, this paper proposes the
Externí odkaz:
https://doaj.org/article/ccd84497de57422a806afc5151d7bd7a
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 5331-5358 (2024)
Abstract Rough fuzzy clustering algorithms have received extensive attention due to the excellent ability to handle overlapping and uncertainty of data. However, existing rough fuzzy clustering algorithms generally consider single view clustering, wh
Externí odkaz:
https://doaj.org/article/ce1f1b470a8546af9f3c30621786c581
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 7, Pp 102129- (2024)
Multi-view graph clustering has garnered tremendous interest for its capability to effectively segregate data by harnessing information from multiple graphs representing distinct views. Despite the advances, conventional methods commonly construct si
Externí odkaz:
https://doaj.org/article/1cab78e3e1994f8dbc73f856eddc6135
Autor:
Golzari Oskouei, Amin a, b, ⁎, Samadi, Negin c, Tanha, Jafar c, Bouyer, Asgarali d, b, Arasteh, Bahman b, e
Publikováno v:
In Neurocomputing 7 February 2025 617
Autor:
Li, Yan a, Hu, Xingchen a, b, ⁎, Zhu, Tuanfei b, c, Liu, Jiyuan a, Liu, Xinwang b, Liu, Zhong a
Publikováno v:
In Information Sciences August 2024 677
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 12, Pp 21098-21119 (2023)
Cancer subtyping (or cancer subtypes identification) based on multi-omics data has played an important role in advancing diagnosis, prognosis and treatment, which triggers the development of advanced multi-view clustering algorithms. However, the hig
Externí odkaz:
https://doaj.org/article/71aaedd1f7634c5db8d8d8ddf44504a6
Publikováno v:
PeerJ Computer Science, Vol 10, p e1906 (2024)
Advances in deep learning have propelled the evolution of multi-view clustering techniques, which strive to obtain a view-common representation from multi-view datasets. However, the contemporary multi-view clustering community confronts two prominen
Externí odkaz:
https://doaj.org/article/2c9cb60a49c648879330a4b65a892d27