RTG: A recursive realistic graph generator using random typing

Data Mining and Knowledge Discovery

Volumn 19, Issue 2, 2009, Pages 194-209

  Akoglu, Leman ^a   Faloutsos, Christos ^a  

^a Carnegie Mellon University   (United States)

Author keywords

Graph generators; Model validation and analysis; Simulation and modeling

Indexed keywords

CROSS PRODUCT; GRAPH GENERATORS; MACROSCOPIC PATTERN; MODEL PARAMETERS; MODEL VALIDATION AND ANALYSIS; REAL-WORLD GRAPHS; REALISTIC GRAPHS; SELF-SIMILAR; SIMULATION AND MODELING; STATIC AND DYNAMIC;

RECURSIVE FUNCTIONS; SIMULATORS;

GRAPH THEORY;

EID: 68749098468     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-009-0140-7     Document Type: Article

References (33)

1. Akoglu L, McGlohon M, Faloutsos C (2008) Rtm: laws and a recursive generator for weighted time-evolving graphs. In: ICDM
2. R Albert H Jeong A-L Barabasi 1999 Diameter of the world wide web Nature 401 130 131
3. AL Barabasi R Albert 1999 Emergence of scaling in random networks Science 286 5439 509 512
4. D Chakrabarti C Faloutsos 2006 Graph mining: laws, generators, and algorithms ACM Comput Surv 38 1 69
5. Chakrabarti D, Zhan Y, Faloutsos C (2004) R-MAT: a recursive model for graph mining. In: Fourth SIAM international conference on data mining, April 2004, Orlando, Florida, USA
6. B Conrad M Mitzenmacher 2004 Power laws for monkeys typing randomly: the case of unequal probabilities IEEE Trans Inf Theory 50 7 1403 1414
7. Crovella M, Bestavros A (1996) Self-similarity in world wide web traffic, evidence and possible causes. In: Sigmetrics, pp 160-169
8. P Erdos A Renyi 1960 On the evolution of random graphs Publ Math Inst Hungary Acad Sci 5 17 61
9. Even-Bar E, Kearns M, Suri S (2007) A network formation game for bipartite exchange economies. In: SODA
10. Fabrikant A, Luthra A, Maneva EN, Papadimitriou CH, Shenker S (2003) On a network creation game. In: PODC
11. Faloutsos M, Faloutsos P, Faloutsos C (1999) On power-law relationships of the internet topology. In: SIGCOMM, pp 251-262
12. GW Flake S Lawrence CL Giles FM Coetzee 2002 Self-organization and identification of web communities IEEE Comput 35 66 71
13. M Girvan MEJ Newman 2002 Community structure in social and biological networks PNAS 99 7821
14. Gomez ME, Santonja V (1998) Self-similarity in i/o workload: analysis and modeling. In: WWC
15. Gribble SD, Manku GS, Roselli D, Brewer EA, Gibson TJ, Miller EL (1998) Self-similarity in file systems. In: SIGMETRICS '98
16. Kleinberg JM, Kumar R, Raghavan P, Rajagopalan S, Tomkins AS (1999) AS The Web as a graph: measurements, models and methods. In: Lecture Notes in Computer Science, vol 1627, pp 1-7
17. Kraetzl MSE, Nickel C (2005) Random dot product graphs: a model for social networks. In: Preliminary manuscript
18. Laoutaris N, Poplawski LJ, Rajaraman R, Sundaram R, Teng S-H (2008) Bounded budget connection (bbc) games or how to make friends and influence people, on a budget. In: PODC
19. Leskovec J, Chakrabarti D, Kleinberg JM, Faloutsos C (2005) Realistic, mathematically tractable graph generation and evolution, using Kronecker multiplication. In: PKDD, Porto, Portugal
20. Leskovec J, Kleinberg J, Faloutsos C (2005) Graphs over time: densification laws, shrinking diameters and possible explanations. In: ACM SIGKDD
21. Mandelbrot B (1953) An informational theory of the statistical structure of language. Commun Theory
22. McGlohon M, Akoglu L, Faloutsos C (2008) Weighted graphs and disconnected components: patterns and a generator. In: ACM SIGKDD, Las Vegas, Aug
23. GA Miller 1957 Some effects of intermittent silence Am J Psychol 70 311 314
24. Newman MEJ (2004) Power laws, Pareto distributions and Zipf's law, December
25. MEJ Newman M Girvan 2004 Finding and evaluating community structure in networks Phys Rev E 69 026113
26. Pennock DM, Flake GW, Lawrence S, Glover EJ, Giles CL (2002) Winners donć6t take all: characterizing the competition for links on the web. In: Proceedings of the national academy of sciences, pp 5207-5211
27. MF Schwartz DCM Wood 1992 Discovering shared interests among people using graph analysis of global electronic mail traffic Commun ACM 36 78 89
28. Siganos G, Faloutsos M, Faloutsos P, Faloutsos C (2003) Power laws and the AS-level internet topology
29. Tsourakakis CE (2008) Fast counting of triangles in large real networks without counting: algorithms and laws. In: ICDM
30. Wang M, Madhyastha T, Chan NH, Papadimitriou S, Faloutsos C (2002) Data mining meets performance evaluation: fast algorithms for modeling bursty traffic. In: ICDE, pp 507-516
31. DJ Watts SH Strogatz 1998 Collective dynamics of 'small-world' networks Nature 393 6684 440 442
32. Young SJ, Scheinerman ER (2007) Random dot product graph models for social networks. In: WAW, pp 138-149
33. Zipf GK (1932) Selective studies and the principle of relative frequency in language. Harvard University Press