In recent years, researchers in graph mining have been exploring linear paths as well as subgraphs as pattern languages. In this paper, we are investigating the middle ground betw...
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the req...
Currently, a large amount of data can be best represented as graphs, e.g., social networks, protein interaction networks, etc. The analysis of these networks is an urgent research ...
Social interactions that occur regularly typically correspond to significant yet often infrequent and hard to detect interaction patterns. To identify such regular behavior, we p...
Existing graph mining algorithms typically assume that databases are relatively static and can fit into the main memory. Mining of subgraphs in a dynamic environment is currently ...