Publication Details
Average Distance Based Method for Association Rules Discovery in Relational Databases
Data mining, association rule, categorical attribute, quantitative attribute,
average distance
The paper describes the new method for association rule discovery in relational
databases, which contain quantitative and categorical attributes. Many methods
have been developed yet. But most of these methods are based on initial
equi-depth discretization of quantitative attributes. These approaches bring the
loss of information. The basic idea of the new method is to separate processing
of categorical and quantitative attributes. The first step finds frequent
k-itemsets containing only values of categorical attributes and then quantitative
attributes are processed one by one. Discretization of values during quantitative
attributes processing is based on a new measure called average distance.
@inproceedings{BUT13997,
author="Vladimír {Bartík}",
title="Average Distance Based Method for Association Rules Discovery in Relational Databases",
booktitle="Proceedings of 6th International Conference ISIM'03 - Information Systems Implementation and Modelling",
year="2003",
pages="161--168",
address="Ostrava",
isbn="80-85988-84-4"
}