Experiments on Graph Clustering Algorithms

By U. Brandes, Marco Gaertler, Dorothea Wagner. Embedded Systems and Applications, 2003

372 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistical and Nonlinear Physics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/79e69b093db23d5c1340076c83a21d434c493c29

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In Artificial Intelligence

In Statistical and Nonlinear Physics

In Signal Processing

Citations in the corpus

Community detection in graphs (2009, methodology): “Zhou defines a “global attractor” of a vertex i to be a closest vertex to i (i. e. any vertex lying at the smallest distance from i), whereas the “local attractor” of i is its closest neighbour.”
Bitcoin Mixing Detection Using Deep Autoencoder (2018, methodology): “We use the measurement in [15] to indicate the quality of the clustering.”
Community Discovery in Dynamic Networks (2017, positive): “The Girvan-Newman benchmark, also known as GN, is built upon the so-called planted l-partition model described in (Brandes et al., 2003; Condon and Karp, 2001; Gaertler et al., 2007) this generator takes as input a given ground truth partition (generated as as equally sized Erdös-Reńyi random graphs”
AliGraph: A Comprehensive Graph Neural Network Platform (2019, background): “, node classification [2], link prediction [35], graph clustering [4], recommendation [51], among many others.”
Fast discovery of connection subgraphs (2004, neutral): “Other related work includes the PageRank [21] and personalized PageRank algorithms [15, 16]; graph clustering, partioning, and matrix reordering [2, 4, 17, 23, 24]; electrical circuits and random walks [3, 7, 22]; and influence propagation [18].”
An Algorithm to Find Overlapping Community Structure in Networks (2007, background): “A wide range of algorithms have been developed to discover communities in a network, including [4, 6, 11, 12, 13, 14].”
Clustering and Community Detection in Directed Networks: A Survey (2013, background): “Moreover, while there are several comparative studies on quality measures for undirected graph clustering [118, 39], similar studies are missing for the directed version of the problem.”