Partial periodic patterns mining with multiple minimum supports

Partial periodic patterns are commonly seen in real-world applications. Most of the previous approaches set a single minimum support threshold for all the events in a sequence. However using only one minimum support for all events in an event sequence to assume they have similar frequencies is not easy to happen in real-life applications. In this paper, we propose an algorithm which applies the projection-based mechanism and specifies multiple minimum supports to effectively discover appropriate partial periodic patterns. Finally, the experimental result shows the good performance of the proposed approach.