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Using the Marshall-Olkin extended Zipf distribution in graph generation

Author
Duarte, A.; Prat-Pérez, A.; Perez-Casany, M.
Type of activity
Book chapter
Book
Using the Marshall-Olkin extended zipf distribution in graph generation
First page
493
Last page
502
Publisher
Springer
Date of publication
2015-12-18
ISBN
978-3-319-27307-5 Open in new window
DOI
https://doi.org/10.1007/978-3-319-27308-2_40 Open in new window
Repository
http://hdl.handle.net/2117/105744 Open in new window
http://hdl.handle.net/2117/105912 Open in new window
URL
https://link.springer.com/chapter/10.1007/978-3-319-27308-2_40 Open in new window
Abstract
Being able to generate large synthetic graphs resembling those found in the real world, is of high importance for the design of new graph algorithms and benchmarks. In this paper, we first compare several probability models in terms of goodness-of-fit, when used to model the degree distribution of real graphs. Second, after confirming that the MOEZipf model is the one that gives better fits, we present a method to generate MOEZipf distributions. The method is shown to work well in practice when ...
Citation
Duarte-López, A., Prat-Pérez, A., Perez-Casany, M. Using the Marshall-Olkin extended Zipf distribution in graph generation. A: "Euro-Par 2015: parallel processing workshops". Berlín: Springer, 2015, p. 493-502.
Keywords
Network analysis, Node degree, Zipf distribution
Group of research
DAMA-UPC - Data Management Group
LARCA - Laboratory of Relational Algorithmics, Complexity and Learnability

Participants