Results 11 to 20 of about 274,931 (209)
Fair Benchmark for Unsupervised Node Representation Learning
Algorithms, 2022 Most machine-learning algorithms assume that instances are independent of each other. This does not hold for networked data. Node representation learning (NRL) aims to learn low-dimensional vectors to represent nodes in a network, such that all ...
Zhihao Guo +6 more
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IEEE Access, 2022 A significant aspect of today’s digital information is attributed networks, which combine multiple node attributes with the basic network topology to extract knowledge.
Wasim Khan +6 more
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Overlapping Community Detection Based on Attribute Augmented Graph
Entropy, 2021 There is a wealth of information in real-world social networks. In addition to the topology information, the vertices or edges of a social network often have attributes, with many of the overlapping vertices belonging to several communities ...
Hanyang Lin +4 more
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Attributed Graph Embedding with Random Walk Regularization and Centrality-Based Attention
Mathematics, 2023 Graph-embedding learning is the foundation of complex information network analysis, aiming to represent nodes in a graph network as low-dimensional dense real-valued vectors for the application in practical analysis tasks.
Yuxuan Yang +4 more
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Clustering of Cancer Attributed Networks via Integration of Graph Embedding and Matrix Factorization
IEEE Access, 2020 Advances in bio-technologies enable the generation of genomic data from various platforms. The accumulated omic data provides an opportunity to exploit the underlying mechanisms of cancers, and imposes a great challenge on designing algorithms for the ...
Qiang Lin, Yong Lin, Qiang Yu, Xiaoke Ma
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Unsupervised community detection in attributed networks based on mutual information maximization
New Journal of Physics, 2021 Community detection is of great significance for understanding network functions and behaviors. With the successful application of deep learning in network-based analyses, recent studies have turned to utilizing graph convolutional networks (GCNs) to ...
Junyou Zhu +4 more
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Leader-Based Community Detection Algorithm in Attributed Networks
IEEE Access, 2021 The community structure plays an indispensable role in developing the deep structure of complex networks. In recent years, some researchers have realized the importance of leader nodes in the community detection process.
Dan-Dan Lu
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Influential Attributed Communities Search in Large Networks (InfACom)
IEEE Access, 2021 Community search is a fundamental problem in graph analysis. In many applications, network nodes have specific properties that are essential for making sense of communities.
Nariman Adel Hussein +2 more
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Bi-pattern mining of attributed networks
Applied Network Science, 2019 Applying closed pattern mining to attributed two-mode networks requires two conditions. First, as in two-mode networks there are two kinds of vertices, each described with a proper attribute set, we have to consider patterns made of two components that ...
Henry Soldano +4 more
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Applied Network Science, 2021 Network analysis provides powerful tools to learn about a variety of social systems. However, most analyses implicitly assume that the considered relational data is error-free, and reliable and accurately reflects the system to be analysed. Especially if
Leonie Neuhäuser +4 more
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