Guest lecture
Pinar Karagoz: Utility Based Mining of Sequential Patterns

Abstract:  High utility sequential pattern mining has been considered as an important research problem and a number of relevant algorithms have been proposed for this topic. The main challenge of high utility sequential pattern mining is that, the search space is large and the efficiency of the solutions is directly affected by the degree at which they can eliminate the candidate patterns. Therefore, the efficiency of any high utility sequential pattern mining solution depends on its ability to reduce this big search space. In this talk, I will present the problem and the techniques to improve pruning of candidate patterns, and then describe a more general framework to define utility in terms of user-defined pattern scoring, applied on web usage data.