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» Graph mining: Laws, generators, and algorithms
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PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
14 years 2 months ago
RTG: A Recursive Realistic Graph Generator Using Random Typing
We propose a new, recursive model to generate realistic graphs, evolving over time. Our model has the following properties: it is (a) flexible, capable of generating the cross pro...
Leman Akoglu, Christos Faloutsos
SDM
2004
SIAM
229views Data Mining» more  SDM 2004»
13 years 9 months ago
R-MAT: A Recursive Model for Graph Mining
How does a `normal' computer (or social) network look like? How can we spot `abnormal' sub-networks in the Internet, or web graph? The answer to such questions is vital ...
Deepayan Chakrabarti, Yiping Zhan, Christos Falout...
ADC
2008
Springer
110views Database» more  ADC 2008»
14 years 1 months ago
Graph Mining based on a Data Partitioning Approach
Existing graph mining algorithms typically assume that the dataset can fit into main memory. As many large graph datasets cannot satisfy this condition, truly scalable graph minin...
Son N. Nguyen, Maria E. Orlowska, Xue Li
PKDD
2005
Springer
155views Data Mining» more  PKDD 2005»
14 years 1 months ago
Realistic, Mathematically Tractable Graph Generation and Evolution, Using Kronecker Multiplication
How can we generate realistic graphs? In addition, how can we do so with a mathematically tractable model that makes it feasible to analyze their properties rigorously? Real graphs...
Jure Leskovec, Deepayan Chakrabarti, Jon M. Kleinb...
IOR
2011
175views more  IOR 2011»
13 years 2 months ago
Clique Relaxations in Social Network Analysis: The Maximum k-Plex Problem
This paper introduces and studies the maximum k-plex problem, which arises in social network analysis and has wider applicability in several important areas employing graph-based ...
Balabhaskar Balasundaram, Sergiy Butenko, Illya V....