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2008
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Measuring extremal dependencies in web graphs

12 years 8 months ago
Measuring extremal dependencies in web graphs
We analyze dependencies in power law graph data (Web sample, Wikipedia sample and a preferential attachment graph) using statistical inference for multivariate regular variation. The well developed theory of regular variation is widely applied in extreme value theory, telecommunications and mathematical finance, and it provides a natural mathematical formalism for analyzing dependencies between variables with power laws. However, most of the proposed methods have never been used in the Web graph data mining. The present work fills this gap. The new insights this yields are striking: the three above-mentioned data sets are shown to have a totally different dependence structure between different graph parameters, such as in-degree and PageRank. Categories and Subject Descriptors: E.1 [Data structures]: Graphs and networks; G.3 [Probability and Statistics]: Multivariate statistics General Terms: Algorithms, Experimentation, Measurement
Yana Volkovich, Nelly Litvak, Bert Zwart
Added 21 Nov 2009
Updated 21 Nov 2009
Type Conference
Year 2008
Where WWW
Authors Yana Volkovich, Nelly Litvak, Bert Zwart
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