Results 11 to 20 of about 156,516 (263)
Data & Knowledge Engineering, 2022 In application domains ranging from social networks to e-commerce, it is important to cluster users with respect to both their relationships (e.g., friendship or trust) and their actions (e.g., visited locations or rated products). Motivated by these applications, we introduce here the task of clustering the nodes of a sequence graph, i.e., a graph ...
H. Zhong (Haodi) +2 more
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Graph Learning for Attributed Graph Clustering
Mathematics, 2022 Due to the explosive growth of graph data, attributed graph clustering has received increasing attention recently. Although deep neural networks based graph clustering methods have achieved impressive performance, the huge amount of training parameters ...
Xiaoran Zhang, Xuanting Xie, Zhao Kang
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Robust Spectral Clustering Incorporating Statistical Sub-Graph Affinity Model
Axioms, 2022 Hyperspectral image (HSI) clustering is a challenging work due to its high complexity. Subspace clustering has been proven to successfully excavate the intrinsic relationships between data points, while traditional subspace clustering methods ignore the ...
Zhenxian Lin, Jiagang Wang, Chengmao Wu
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Graph Clustering with Graph Neural Networks
J. Mach. Learn. Res., 2020 Graph Neural Networks (GNNs) have achieved state-of-the-art results on many graph analysis tasks such as node classification and link prediction. However, important unsupervised problems on graphs, such as graph clustering, have proved more resistant to advances in GNNs.
Anton Tsitsulin +3 more
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An Efficient Vertex-Driven Temporal Graph Model and Subgraph Clustering Method
IEEE Access, 2022 The temporal graph can represent a temporal relationship widely used in compound synthesis analysis, biological gene analysis, etc. However, the temporal graph would embody vertex updates frequently, high time resolution, and not enumerated rules.
Hanlin Zhang +4 more
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Multi-view Attributed Graph Clustering Based on Contrast Consensus Graph Learning [PDF]
Jisuanji kexueMulti-view attribute graph clustering can divide nodes of graph data with multiple views into different clusters,which has attracted widespread attention from researchers in recent years.At present,many multi-view attribute graph clustering me-thods ...
LIU Pengyi, HU Jie, WANG Hongjun, PENG Bo
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Multi-view Graph Clustering Algorithm Based on Dual Contrastive Learning and Hard Sample Mining [PDF]
Jisuanji gongchengAs a key research direction in the field of graph mining, graph clustering aims to discover substructures or node groups with similarities from graph data and classify them into the same cluster.
QIAN Lifeng, LI Jing, ZOU Xuxi, CHEN Yu, GU Yalin, WEI Xunhu
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Frontiers in Genetics, 2021 It is a vital task to design an integrated machine learning model to discover cancer subtypes and understand the heterogeneity of cancer based on multiple omics data.
Jian Liu +7 more
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Random Graphs with Clustering [PDF]
Physical Review Letters, 2009 We offer a solution to a long-standing problem in the physics of networks, the creation of a plausible, solvable model of a network that displays clustering or transitivity -- the propensity for two neighbors of a network node also to be neighbors of one another.
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Graph-based data clustering via multiscale community detection
Applied Network Science, 2020 We present a graph-theoretical approach to data clustering, which combines the creation of a graph from the data with Markov Stability, a multiscale community detection framework. We show how the multiscale capabilities of the method allow the estimation
Zijing Liu, Mauricio Barahona
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