Rough Sets and Association Rule Generation

Article type: Research Article

Authors: Nguyen, Hung Son | Nguyen, Sinh Hoa

Affiliations: Institute of Mathematics, Warsaw University, Banacha Str. 2, 02-095, Warsaw Poland. e-mail: [email protected]; [email protected]

Note: [] Address for correspondence: Hung Son Nguyen, Institute of Mathematics, Warsaw University, ul. Banacha 2, 02-095, Warsaw Poland

Abstract: ASSOCIATION RULE (see [1]) extraction methods have been developed as the main methods for mining of real life data, in particular in Basket Data Analysis. In this paper we present a novel approach to generation of association rules, based on Rough Set and Boolean reasoning methods. Some results presented in this paper has been mentioned in [13, 17]. We will explain them precisely (with full proofs of theorems) in this paper. We show the relationship between the problems of association rule extraction for transaction data and relative reducts (or α-reducts generation) for a decision table. Moreover, the present approach can be used to extract association rules in general form. The experimental results show that the presented methods are quite efficient. Large number of association rules with given support and confidence can be extracted in a short time.

DOI: 10.3233/FI-1999-40403

Journal: Fundamenta Informaticae, vol. 40, no. 4, pp. 383-405, 1999