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pro vyhledávání: '"Community detection in graphs"'
Akademický článek
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Autor:
Li, Jiakang, Lai, Songning, Shuai, Zhihao, Tan, Yuan, Jia, Yifan, Yu, Mianyang, Song, Zichen, Peng, Xiaokang, Xu, Ziyang, Ni, Yongxin, Qiu, Haifeng, Yang, Jiayu, Liu, Yutong, Lu, Yonggang
The study of complex networks has significantly advanced our understanding of community structures which serves as a crucial feature of real-world graphs. Detecting communities in graphs is a challenging problem with applications in sociology, biolog
Externí odkaz:
http://arxiv.org/abs/2309.11798
The main goal of the multitasking optimization paradigm is to solve multiple and concurrent optimization tasks in a simultaneous way through a single search process. For attaining promising results, potential complementarities and synergies between t
Externí odkaz:
http://arxiv.org/abs/2009.14477
Autor:
Belim, S. V., Larionov, S. B.
Publikováno v:
2017 Dynamics of Systems, Mechanisms and Machines (Dynamics), Omsk, Russia, pp. 1-5
This article suggests an algorithm of impulse noise filtration, based on the community detection in graphs. The image is representing as non-oriented weighted graph. Each pixel of an image is corresponding to a vertex of the graph. Community detectio
Externí odkaz:
http://arxiv.org/abs/1812.10098
Autor:
Linares, Oscar A. C., Botelho, Glenda Michele, Rodrigues, Francisco Aparecido, Neto, João Batista
Image segmentation has many applications which range from machine learning to medical diagnosis. In this paper, we propose a framework for the segmentation of images based on super-pixels and algorithms for community identification in graphs. The sup
Externí odkaz:
http://arxiv.org/abs/1612.03705
Publikováno v:
IEEE Access, Vol 9, Pp 118757-118770 (2021)
Community detection in network-type data provides a powerful tool in analyzing and understanding real-world systems. In fact, community detection approaches aim to reduce the network’s dimensionality and partition it into a set of disjoint clusters
Externí odkaz:
https://doaj.org/article/0c1dbf3145c645b48bf958b107fbab9f
Publikováno v:
IEEE Access, Vol 8, Pp 139096-139109 (2020)
The notion of k-truss has been introduced a decade ago in social network analysis and security for community detection, as a form of cohesive subgraphs less stringent than a clique (set of pairwise linked nodes), and more selective than a k-core (ind
Externí odkaz:
https://doaj.org/article/d87f02ab378a4586ae1a540d2470109e
We study a class of discrete-time multi-agent systems modelling opinion dynamics with decaying confidence. We consider a network of agents where each agent has an opinion. At each time step, the agents exchange their opinion with their neighbors and
Externí odkaz:
http://arxiv.org/abs/0911.5239
Autor:
Fortunato, Santo
Publikováno v:
Physics Reports 486, 75-174 (2010)
The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices i
Externí odkaz:
http://arxiv.org/abs/0906.0612
Akademický článek
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