An Effective Mining Algorithm for Weighted Association Rules in Communication Networks

Abstract

The mining of weighted association rules is one of the primary methods used in communication alarm correlation analysis. With large communication alarm database, the traditional methods often treated each item evenly that makes the process of mining association rules time consuming. To improve the efficiency, items appearing in transactions are weighted using the analytic hierarchy process to reflect the importance of them which is more meaningful in some application. This paper implements a fast and stable algorithm to mining weighted association rules based on ISS(item sequence sets). Experiments on performance study will prove the superiority of the new algorithm.