We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
The discovery of subsets with special properties from binary data has been one of the key themes in pattern discovery. Pattern classes such as frequent itemsets stress the co-occu...
Eino Hinkkanen, Hannes Heikinheimo, Heikki Mannila...