Biosequences typically have a small alphabet, a long length, and patterns containing gaps (i.e., “don’t care”) of arbitrary size. Mining frequent patterns in such sequences ...
Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utiliz...
Themis P. Exarchos, Costas Papaloukas, Christos La...
Since point and click at web pages generate continuous data stream, which flow into web log data, old patterns may be stale and need to be updated. Algorithms for mining web seque...
Mining data warehouses is still an open problem as few approaches really take the specificities of this framework into account (e.g. multidimensionality, hierarchies, historized ...
Marc Plantevit, Anne Laurent, Maguelonne Teisseire
The main challenge of mining sequential patterns is the high processing cost of support counting for large amount of candidate patterns. For solving this problem, SPAM algorithm wa...