Special Issue of Infor on Rough Sets And Web-Based Systems In Decision Support

Explosion of the Internet and the Internet-based activities observed in the last decade has had significant impact on research agenda at the universities. This special issue on Rough Sets and Web-based systems in decision support deals only with a very selected set of topics in the area. Its focus is on the analysis of decision problems from the point of view of clarity of their description (often obscured by massive amount of information available to a decision-maker) and on support of a decision-making activity with Webbased tools. The research presented in this issue was first reported at the Decision Analysis and Support Workshop held in December 1998 at the International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria. In 1995 a group of Canadian researchers from Carleton University in Ottawa, together with their Finnish colleagues and scientists from several other countries undertook an initiative to establish joint methodological project at IIASA. Their proposal was accepted and the Decision Analysis and Support (DAS) Project started in July 1997-̂ . The DAS project was a continuation of IIASA's tradition in methodological research in decision science and its computational support. It complemented other IIASA activities involving mediumand large-scale population analysis, energy, and environmental and sustainable development research aiming at both developed and developing countries. The Canadian scientists contributions to the DAS project included the use of data mining techniques for the analysis of forestry data, development of Web-based tools for training in international trade and business negotiations, and construction of a software agent prototype for ecommerce. The project's members organized five international workshops, one of them in cooperation with the International Development Research Centre Canada (IDRC). The workshops dealt with numerous issues faced by the researchers and practitioners of the decision analysis and support and involved participants from over 15 countries. This special issue is intended to emphasize some ofthe research trends studied by the DAS Project and discussed at the DAS workshops. Due to the usual space limitations of a scientific publication, it is not an exhaustive review of all the research activities conducted by the DAS scientists and collaborators. The first paper in the issue provides a general overview of the methodological and theoretical issues associated with the Rough Sets analysis of imprecise data. Pawlak, who is the original author of this methodology, discusses significance of Rough Sets for the evaluation of different aspects ofthe decision processes. He illustrates this discussion with intuitive examples. Greco, Matarazzo and Slowinski describe how the Rough Sets approach can be applied to the muiticriteria sorting problem. They present extensions to the theory that allow dealing with such classical decision problems as sorting, choice, or ranking. Their results are illustrated with a case study of an airline company s financial ratings. Tsumoto in his paper is concerned with the rule induction problem where extracted rules do not plausibly represent information on experts decision processes. Using the Rough Sets principles he proposes a rule induction method that is successfully tested on medical database resulting in a discovery of interesting patterns in data.