Earticle

Periodic pattern mining has gained a great attention in the past decade. Previous studies mostly focus on synchronous periodic patterns. The literature proposes many methods for mining periodic patterns. Nevertheless, asynchronous periodic pattern mining has gradually received more attention recently. In this paper, we propose an efficient 2-D linked structure and the OEOP (One Event One Pattern) algorithm to discover all kinds of valid segments in each single event sequence. Then, referring to the general model of asynchronous periodic pattern mining proposed by Huang and Chang, this study combines these valid segments found by OEOP into 1-patterns with multiple events, multiple patterns with multiple events and asynchronous periodic patterns. The experimental results show that these algorithms have good performance and scalability.

Research on periodic pattern mining has gained a great attention in the past decade. Periodic pattern mining discovers valid periodic patterns in a time-related dataset. This study proposed an efficient 2-D linked structure and the OEOP (One Event One Pattern) algorithm to discover all kinds of valid segments in each single event sequence. Then, this study combines these valid segments found by OEOP into 1-patterns with multiple events, and multiple patterns with multiple events periodic patterns. The experimental results show that the proposed algorithm has good performance and scalability.