Affiliations: [a] Graduate School of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu, Japan | [b] Faculty of Management and Information Science, Josai International University, Togane, Chiba, Japan
Corresponding author: Hiroshi Sakai, Graduate School of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu 804-8550, Japan. Tel.: +81 93 884 3258; E-mail:[email protected]
Abstract: This paper proposes granules for association rules in
Deterministic Information Systems (DISs) and
Non-deterministic Information Systems (NISs).
Granules for an association rule are defined for every implication,
and give us a new methodology for knowledge discovery and decision support.
We see that decision support based on a table under the condition P is to fix
the decision Q by using the most proper association rule P\Rightarrow Q.
We recently implemented a system getRNIA powered by granules for association rules.
This paper describes how the getRNIA system deals with decision support under uncertainty,
and shows some results of the experiment.
Keywords: Granules, rough sets, association rules, software, incomplete information, non-deterministic information