Association rule mining is concerned with the discovery of interesting association relationships hidden in databases. Existing algorithms typically assume that data characteristics are stable over time. Their main focus is therefore to mine association rules in an efficient manner. However, the world constantly changes. This makes the characteristics of real-life entities represented by the dat...

There are many various methods to forecast time series. However, there is no single forecasting method that generally outperforms any other. Consequently, there always exists a danger of choosing a method that is inappropriate for a given time series. To overcome such a problem, distinct ensemble techniques are being proposed. These techniques combine more individual forecasting methods. In thi...

One of the most well-studied problems in data mining is mining for association rules. There was also research that introduced association rule mining methods to conduct classification tasks. These classification methods, based on association rule mining, could be applied for customer segmentation. Currently, most of the association rule mining methods are based on a supportconfidence structure,...