Fast discovery of connection subgraphs

By Christos Faloutsos, Kevin S. McCurley, Andrew Tomkins. Knowledge Discovery and Data Mining, 2004

408 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/c7c80da5f576b293bd02ce305453e2adef6cc0de

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In Artificial Intelligence

In Computer Networks and Communications

In Statistical and Nonlinear Physics

Citations in the corpus

Link prediction using supervised learning (2006, background): “[3], although not directly performs link prediction, is worth mentioning in this context.”
Fast Random Walk with Restart and Its Applications (2006, methodology): “There are several methods similar to RWR, including electricitybased method [28], graph-based Semi-supervised learning [27] [7] and so on.”
POLYPHONET: an advanced social network extraction system from the web (2006, background): “[14] obtain a social network of 15 million persons from 500 million Web pages using their cooccurrence within a window of 10 words.”
Graph based anomaly detection and description: a survey (2014, methodology): “The original method in [Faloutsos et al., 2004] is based on the so-called delivered current.”
Fast Random Walk Graph Kernel (2012, background): “, random walk with restart [27, 39], sinkaugmented delivered current [8], cycle free effective conductance [22], survivable network [13], direction-aware proximity [38], ObjectRank [2], RelationalRank [11], SimRank [18] and its fast approximation [24] Low-Rank Approximation.”
The community-search problem and how to plan a successful cocktail party (2010, background): “Such measures are based on electrical-current flows [10] and the related notion of random walks [28].”
Random walk with restart: fast solutions and applications (2008, methodology): “There are several methods similar to RWR, including electricity-basedmethod[31],graph-basedSemi-supervisedlearning[ 7 ,30]andsoon.Exact solution of these methods usually requires the inversion of a matrix which is often diagonal dominant and of big size.”
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 sub-graph discovery [23].”
Trains of thought: generating information maps (2012, background): “Graph representations are common across a variety of related problems [Jo et al., 2011, Faloutsos et al., 2004, Nallapati et al., 2004] , from topic evolution to news analysis.”