Multidimensional Association Rules on Tensors

Abstract

In this work, we propose a framework suitable for multidimensional data mining based on tensor. A Tensor Data Model (TDM) provides us with high order data structure and naive description for information retrieval. Among others, we discuss multidimensional rule mining here. Generally, association rule mining (or extraction of association rules) concerns about co-related transaction records of single predicate, and hard to examine the ones over multiple predicates since it takes heavy timeand spacecomplexities. Here we show TDM allows us to model several operations specific to multidimensional data mining yet to reduce amount of description.