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 ...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
In the past, quite a few fast algorithms have been developed to mine frequent patterns over graph data, with the large spectrum covering many variants of the problem. However, the...
In this paper, we investigate a new approach for literature mining. We use frequent subgraph mining, and its generalization topological structure mining, for finding interesting re...
Fan Wang, Ruoming Jin, Gagan Agrawal, Helen Piontk...
Large graph databases are commonly collected and analyzed in numerous domains. For reasons related to either space efficiency or for privacy protection (e.g., in the case of socia...