An Entropy-Based Approach for Generating Multi-dimensional Sequential Patterns

摘要

This paper proposes a new method for generating multidimensional sequential patterns. While the current sequential pattern methods are generating patterns within a single attribute, the proposed method is able to detect them among different attributes. We employ an information theoretic method for generating multi-dimensional sequential patterns with the use of Hellinger entropy measure. A number of theorems are proposed to reduce the computational complexity of the sequential pattern systems. The proposed method is tested on some synthesized transaction databases.