Title

Discovering Calendar-Based Temporal Association Rules

Publication Type

Journal Article

Publication Date

2003

Abstract

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.

Discipline

Information Security

Research Areas

Information Security and Trust

Publication

Data and Knowledge Engineering

Volume

44

Issue

2

First Page

193

Last Page

218

ISSN

0169-023X

Identifier

10.1016/s0169-023x(02)00135-0

Publisher

Elsevier

Additional URL

http://dx.doi.org/10.1016/s0169-023x(02)00135-0