Towards an incremental maintenance of cyclic association rules

Recently, the cyclic association rules have been introduced in order to discover rules from items characterized by their regular variation over time. In real life situations, temporal databases are often appended or updated. Rescanning the whole database every time is highly expensive while existing incremental mining techniques can efficiently solve such a problem. In this paper, we propose an incremental algorithm for cyclic association rules maintenance. The carried out experiments of our proposal stress on its efficiency and performance.