Center-piece subgraphs: problem definition and fast solutions

By Hanghang Tong, Christos Faloutsos. Knowledge Discovery and Data Mining, 2006

305 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/0e88a4e565d8bd9a541b608e541e284dac963daa

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In Artificial Intelligence

In Molecular Biology

In Statistical and Nonlinear Physics

Citations in the corpus

Random walk with restart: fast solutions and applications (2008, methodology): “In [29], the authors also propose penalizing the famous nodes before row normalization for social network.”
Graph Clustering Based on Structural/Attribute Similarities (2009, background): “Other studies which use random walk with restarts include connection subgraph discovery [7] and center-piece subgraph discovery [23].”
Generative Image Segmentation Using Random Walks with Restart (2008, methodology): “It has good performance on many other applications: Cross-model correlation discovery [8], Center-piece subgraph discovery [13], Content based image retrieval [12], Neighborhood formulation [14] and etc.”
The community-search problem and how to plan a successful cocktail party (2010, background): “[28], as well as other researchers have studied the problem of finding a subgraph that connects a set of query nodes in a graph.”
Supervised random walks: predicting and recommending links in social networks (2010, background): “Random walks on graphs have been considered for computing node proximities in large graphs [31, 30, 29, 27].”
Fast Random Walk with Restart and Its Applications (2006, methodology): “B LIN is used to generate 1000 candidates, which are further fed to the original Ceps Algorithm [26] to generate the final center-piece s ubgraphs.”
Graph based anomaly detection and description: a survey (2014, methodology): “CenterPiece Subgraphs (CEPS) [Tong and Faloutsos, 2006] generalizes this by considering the following settings: Given Q query nodes in a social network (e.g., a set of topranked authors in a co-authorship network), find the node(s) and the resulting subgraph, that have strong connections to all or…”
K-isomorphism: privacy preserving network publication against structural attacks (2010, background): “There are also different kinds of querying or knowledge discovery processing on social networks [17, 14, 25, 6, 5].”