An Asynchronous Periodic Sequential Pattern Mining Algorithm with Multiple Minimum Item Supports for Ad Hoc Networking

Abstract

The original sequential pattern mining model only considers occurrence frequencies of sequential patterns, disregarding their occurrence periodicity. We propose an asynchronous periodic sequential pattern mining model to discover the sequential patterns that not only occur frequently but also appear periodically. For this mining model, we propose a pattern-growth mining algorithm to mine asynchronous periodic sequential patterns with multiple minimum item supports. This algorithm employs a divide-and-conquer strategy to mine asynchronous periodic sequential patterns in a depth-first manner recursively. We describe the process of algorithm realization and demonstrate the efficiency and stability of the algorithm through experimental results.