Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
Andreas Maunz, Christoph Helma, Tobias Cramer, Ste...
The shear volume of the results in traditional support based frequent sequential pattern mining methods has led to increasing interest in new intelligent mining methods to find mo...
In the domain of bioinformatics, the role played in the biological process by proteins, that act as transmitters and receivers of information thus ruling the mechanisms that deter...
The mining of periodic patterns in time series databases is an interesting data mining problem that can be envisioned as a tool for forecasting and predicting the future behavior o...
Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagar...
Data stream analysis frequently relies on identifying correlations and posing conditional queries on the data after it has been seen. Correlated aggregates form an important examp...