Title: Association rule-based decision making in table data

Authors: Hiroshi Sakai; Mao Wu; Michinori Nakata

Addresses: Department of Basic Sciences, Faculty of Engineering, Kyushu Institute of Technology, Sensui 1-1, Tobata, Kitakyushu 804, Japan. ' Department of Integrated System Engineering, School of Engineering, Kyushu Institute of Technology, Sensui 1-1, Tobata, Kitakyushu 804, Japan. ' Faculty of Management and Information Science, Josai International University, Gumyo, Togane, Chiba 283, Japan

Abstract: We have been coping with several aspects of rough sets in non-deterministic information systems (NISs) and tables with inexact data. We are simply calling this work rough non-deterministic information analysis (RNIA). As for decision making in RNIA, we at first obtain rules in tables, then we apply them to the current condition. Therefore, there may be a case that the current condition may not match with the condition part in the obtained rules. In order to recover this unmatched case, this paper newly considers direct question-answering in tables, and proposes association rule-based decision making in tables. The validity of the decision is defined by the criterion values of the association rule. This decision making recovers the complementary functionality in the application of obtained rules. Some examples of execution by the implemented software tool are also presented.

Keywords: decision making; rough sets; association rules; non-deterministic information systems; incomplete information; intervals; inexact data.

DOI: 10.1504/IJRIS.2012.050374

International Journal of Reasoning-based Intelligent Systems, 2012 Vol.4 No.3, pp.162 - 170

Published online: 16 Nov 2012 *

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