Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from...
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...
Transactional data are ubiquitous. Several methods, including frequent itemsets mining and co-clustering, have been proposed to analyze transactional databases. In this work, we p...
Yang Xiang, Ruoming Jin, David Fuhry, Feodor F. Dr...
In this paper we introduce a new type of pattern – a flipping correlation pattern. The flipping patterns are obtained from contrasting the correlations between items at diffe...
Marina Barsky, Sangkyum Kim, Tim Weninger, Jiawei ...