HADI: Mining radii of large graphs (2010)
| Venue: | ACM Transactions on Knowledge Discovery from Data |
| Citations: | 9 - 4 self |
BibTeX
@ARTICLE{Kang10hadi:mining,
author = {U Kang and Charalampos E. Tsourakakis and Ana Paula Appel and Usp At São Carlos and Christos Faloutsos},
title = {HADI: Mining radii of large graphs},
journal = {ACM Transactions on Knowledge Discovery from Data},
year = {2010}
}
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Abstract
Given large, multi-million node graphs (e.g., Facebook, web-crawls, etc.), how do they evolve over time? How are they connected? What are the central nodes and the outliers? In this paper we define the Radius plot of a graph and show how it can answer these questions. However, computing the Radius plot is prohibitively expensive for graphs reaching the planetary scale. There are two major contributions in this paper: (a) We propose HADI (HAdoop DIameter and radii estimator), a carefully designed and fine-tuned algorithm to compute the radii and the diameter of massive graphs, that runs on the top of the Hadoop/MapReduce system, with excellent scale-up on the number of available machines (b) We run HADI on several real world datasets including YahooWeb (6B edges, 1/8 of a Terabyte), one of the largest public graphs ever analyzed. Thanks to HADI, we report fascinating patterns on large networks, like the surprisingly small effective diameter, the multi-modal/bi-modal shape of the Radius plot, and its palindrome motion over time.
