Mining association rules in tree structured XML data

Abstract

XML is increasingly popular for knowledge representations. However, mining association rules from them is a challenging issue since XML data is usually poorly supported by the current database systems due to its tree structure. Several encouraging attempts at developing methods for mining rules in tree dataset have been proposed, but simplicity and efficiency still remain significant impediments for further development. What is needed is a clear and simple methodology for finding the rules that are hidden in the heterogeneous tree data. In this paper, we adjust and fine-tune the label projection method which has been recently published to compute association rules from trees. The suggested approach avoids the computationally intractable problem caused by the number of nodes contained in the tree dataset.