Efficient Incremental Breadth-Depth XML Event Mining

TL;DR

This paper introduces an efficient method for mining frequent events and association rules from large XML-logged data using a novel tree structure called FXT, enabling single-pass construction and fast querying.

Contribution

It proposes a new FXT structure for incremental XML event mining and demonstrates its efficiency in constructing and querying for frequent patterns.

Findings

FXT enables single-pass construction from logged data.

The algorithm efficiently discovers frequent itemsets and rules.

Performance studies confirm the method's efficiency.

Abstract

Many applications log a large amount of events continuously. Extracting interesting knowledge from logged events is an emerging active research area in data mining. In this context, we propose an approach for mining frequent events and association rules from logged events in XML format. This approach is composed of two-main phases: I) constructing a novel tree structure called Frequency XML-based Tree (FXT), which contains the frequency of events to be mined; II) querying the constructed FXT using XQuery to discover frequent itemsets and association rules. The FXT is constructed with a single-pass over logged data. We implement the proposed algorithm and study various performance issues. The performance study shows that the algorithm is efficient, for both constructing the FXT and discovering association rules.