Hierarchical clustering and association rule discovery process for efficient decision support system

Abstract

This paper proposed a model based on hierarchical Clustering and Association Rule, which is intended for decision support system. The proposed system is intended to address the shortcomings of other data mining tools on the processing time and efficiency when generating association rules. This study will determine the data structures by implementing the cluster analysis which is integrated in the proposed architecture for data mining process and calculate for associations based on clustered data. The results were obtained using the proposed system as integrated approach and were rendered on the synthetic data. Although, our implementation uses heuristic approach, the experiment shows that the proposed system generated good and understandable association rules, which could be practically explained and use for the decision support purposes.