Mining Closed Discriminative Dyadic Sequential Patterns

A lot of data are in sequential formats. In this paper, the authors are interested in sequential data that goes in pairs. There are many interesting datasets in this format coming from various domains including parallel textual corpora, duplicate bug reports, and other pairs of related sequences of events. Their goal is to mine a set of closed discriminative dyadic sequential patterns from a database of sequence pairs each belonging to one of the two classes +ve and -ve. These dyadic sequential patterns characterize the discriminating facets contrasting the two classes. They are potentially good features to be used for the classification of dyadic sequential data.