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...
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Mining graph data is an increasingly popular challenge, which has practical applications in many areas, including molecular substructure discovery, web link analysis, fraud detect...
—Bibliographic databases are a prosperous field for data mining research and social network analysis. They contain rich information, which can be analyzed across different dimen...
In this paper, we study efficient closed pattern mining in a general framework of set systems, which are families of subsets ordered by set-inclusion with a certain structure, pro...