In this paper, we present a framework for mining diverging patterns, a new type of contrast patterns whose frequency changes significantly differently in two data sets, e.g., it c...
Increased availability of large repositories of chemical compounds has created new challenges and opportunities for the application of data-mining and indexing techniques to probl...
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...
Sequential pattern mining is very important because it is the basis of many applications. Yet how to efficiently implement the mining is difficult due to the inherent characteri...
Graph structure can model the relationships among a set of objects. Mining quasi-clique patterns from large dense graph data makes sense with respect to both statistic and applica...