Results 11 to 20 of about 1,256,700 (250)
The clustering coefficient of a scale-free random graph [PDF]
, 2009 We consider a random graph process in which, at each time step, a new vertex is added with m out-neighbours, chosen with probabilities proportional to their degree plus a strictly positive constant.
Eggemann, N, Noble, S D
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Contrastive and attentive graph learning for multi-view clustering
, 2022 Graph-based multi-view clustering aims to take advantage of multiple view graph information to provide clustering solutions. The consistency constraint of multiple views is the key of multi-view graph clustering.
Li, Lin +9 more
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A survey of kernel and spectral methods for clustering [PDF]
, 2007 Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with a special interest in two recent approaches: kernel and spectral methods ...
Masulli, F. +11 more
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Trio-based collaborative multi-view graph clustering with multiple constraints
, 2021 Multi-view graph clustering is an attentional research topic in recent years due to its wide applications. According to recent surveys, most existing works focus on incorporating comprehensive information among multiple views to achieve the clustering ...
Li, Lin +11 more
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Ensemble clustering via heuristic optimisation [PDF]
, 2010 This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityTraditional clustering algorithms have different criteria and biases, and there is no single algorithm that can be the best solution for a wide range of ...
Li, Jian
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Large scale clustering of protein sequences with FORCE - a layout based heuristic for weighted cluster editing [PDF]
, 2007 Wittkop T, Baumbach J, Lobo FP, Rahmann S. Large scale clustering of protein sequences with FORCE - a layout based heuristic for weighted cluster editing. BMC Bioinformatics.
Wittkop, Tobias +11 more
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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
doaj +1 more source
Node-attribute graph layout for small-world networks [PDF]
, 2011 Small-world networks are a very commonly occurring type of graph in the real-world, which exhibit a clustered structure that is not well represented by current graph layout algorithms. In many cases we also have information about the nodes in such graphs,
Joe Faith +3 more
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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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Adaptive Graph Convolution Using Heat Kernel for Attributed Graph Clustering
Applied Sciences, 2020 Attributed graphs contain a lot of node features and structural relationships, and how to utilize their inherent information sufficiently to improve graph clustering performance has attracted much attention.
Danyang Zhu +3 more
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