Computational Information Geometry Wonderland

In the ICDE'06 paper:

MIC Framework: An Information-Theoretic Approach to Quantitative Association Rule Mining

The authors present an efficient system for finding out quantitative association rules (QARs) by wise combinatorial enumeration in graph with edges built if and only if the corresponding vertices have a good normalized mutual information.

The normalized mutual information is defined as:

The paper makes mention of an article of Sergey Brin, that is well cited (over 150+) on citeseer. This paper defines a notion of interestingness of an association rule.

The question remains open to find out the geometry and axiomatic approach of defining good rules in data mining...