Discovering Calendar-Based Temporal Association Rules

• Main Authors: LI, Yingjiu, Ning, Peng, WANG, X. Sean, Jajodia, Sushil
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2003
• Subjects: Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/59; http://dx.doi.org/10.1016/s0169-023x(02)00135-0
• Institution: Singapore Management University

We study the problem of mining association rules and related time intervals, where an association rule holds either in all or some of the intervals. To restrict to meaningful time intervals, we use calendar schemas and their calendar-based patterns. A calendar schema example is (year, month, day) and a calendar-based pattern within the schema is (*, 3, 15), which represents the set of time intervals each corresponding to the 15th day of a March. Our focus is finding efficient algorithms for this mining problem by extending the well-known Apriori algorithm with effective pruning techniques. We evaluate our techniques via experiments.