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WAW
2007
Springer
157views Algorithms» more  WAW 2007»
14 years 1 months ago
Stochastic Kronecker Graphs
A random graph model based on Kronecker products of probability matrices has been recently proposed as a generative model for large-scale real-world networks such as the web. This...
Mohammad Mahdian, Ying Xu 0002
FASE
2005
Springer
14 years 27 days ago
Ensuring Structural Constraints in Graph-Based Models with Type Inheritance
Graphs are a common means to represent structures in models and meta-models of software systems. In this context, the description of model domains by classifying the domain entitie...
Gabriele Taentzer, Arend Rensink
PVLDB
2008
116views more  PVLDB 2008»
13 years 6 months ago
Anonymizing bipartite graph data using safe groupings
Private data often comes in the form of associations between entities, such as customers and products bought from a pharmacy, which are naturally represented in the form of a larg...
Graham Cormode, Divesh Srivastava, Ting Yu, Qing Z...
ICML
2007
IEEE
14 years 8 months ago
Scalable modeling of real graphs using Kronecker multiplication
Given a large, real graph, how can we generate a synthetic graph that matches its properties, i.e., it has similar degree distribution, similar (small) diameter, similar spectrum,...
Jure Leskovec, Christos Faloutsos
ML
2010
ACM
185views Machine Learning» more  ML 2010»
13 years 2 months ago
Learning to rank on graphs
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...
Shivani Agarwal