We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
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...
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
Abstract. Recent studies demonstrating the existence of special non-coding "antisense" RNAs used in post-transcriptional gene regulation have received considerable attent...