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PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 11 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 10 months ago
Mobile call graphs: beyond power-law and lognormal distributions
We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distr...
Mukund Seshadri, Sridhar Machiraju, Ashwin Sridhar...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
14 years 10 months ago
Group formation in large social networks: membership, growth, and evolution
The processes by which communities come together, attract new members, and develop over time is a central research issue in the social sciences -- political movements, professiona...
Lars Backstrom, Daniel P. Huttenlocher, Jon M. Kle...
KDD
2005
ACM
140views Data Mining» more  KDD 2005»
14 years 10 months ago
Graphs over time: densification laws, shrinking diameters and possible explanations
How do real graphs evolve over time? What are "normal" growth patterns in social, technological, and information networks? Many studies have discovered patterns in stati...
Jure Leskovec, Jon M. Kleinberg, Christos Faloutso...
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 10 months ago
Predicting customer shopping lists from point-of-sale purchase data
This paper describes a prototype that predicts the shopping lists for customers in a retail store. The shopping list prediction is one aspect of a larger system we have developed ...
Chad M. Cumby, Andrew E. Fano, Rayid Ghani, Marko ...