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RTG: A Recursive Realistic Graph Generator Using Random Typing

  • Leman Akoglu
  • Christos Faloutsos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5781)

Abstract

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 product of weighted/ unweighted, directed/undirected, uni/bipartite graphs; (b) realistic, giving graphs that obey eleven static and dynamic laws that real graphs follow (we formally prove that for several of the (power) laws and we estimate their exponents as a function of the model parameters); (c) parsimonious, requiring only four parameters. (d) fast, being linear on the number of edges; (e) simple, intuitively leading to the generation of macroscopic patterns. We empirically show that our model mimics two real-world graphs very well: Blognet (unipartite, undirected, unweighted) with 27K nodes and 125K edges; and Committee-to-Candidate campaign donations (bipartite, directed, weighted) with 23K nodes and 880K edges. We also show how to handle time so that edge/weight additions are bursty and self-similar.

Keywords

Degree Distribution Graph Generator Output Graph Campaign Donation Unique Word 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Leman Akoglu
    • 1
  • Christos Faloutsos
    • 1
  1. 1.School of Computer ScienceCarnegie Mellon UniversityUSA

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