Two machine-learning techniques for mining solutions of the ReleasePlanner™ decision support system

In this paper, two machine-learning techniques, called rough set analysis (RSA) and dependency network analysis (DNA), are proposed for mining DSS solutions. The mining results are provided to the users as explanations for those solutions. Two parts of research results are described. First, a framework applying RSA and DNA for generating explanations for DSS solutions is presented. This framework is generic and applicable to many other DSSs. Second, as a proof-of-concept, the applications of RSA and DNA techniques are demonstrated through a case study of mining patterns from input-output pairs of ReleasePlanner™, a specific DSS for product release planning. Our evaluation indicates that the explanations generated by RSA and DNA improve the overall user acceptance of results provided by this specific DSS.