http://repub.eur.nl/res/aut/14743/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/12588/ 1999-01-01T00:00:00Z http://repub.eur.nl/res/pub/18105/ 1998-01-01T00:00:00Z Object-oriented (00) frameworks are considered an important step forward in developing software applications efficiently. Success of frameworks has however predominantly been limited to structured domains.This paper describes a method for developing 00 domainframeworks for semi-structured domains. The complexityof such domains requires the use of more elaborate analysis and design techniques than those normallyused in 00 analysis and design. In the method describedhere, the knowledge of domain experts forms the basis for developing the framework. The 00 framework is constructed on the design level using a CASE-tool.Using the design model, the framework can be customized and extended to develop a variety of applicationsfor the domain. The approach is illustrated by developing a framework for the sales-promotions domain,and using this framework to build an application for product managers. It is concluded that the approach described here is beneficial to build and use 00 frameworksfor semi-structured domains. http://repub.eur.nl/res/pub/12500/ 1997-01-01T00:00:00Z http://repub.eur.nl/res/pub/12502/ 1997-01-01T00:00:00Z Over the past decade, case-based reasoning (CBR) has emerged as a major research area within the artificial intelligence research field due to both its widespread usage by humans and its appeal as a methodology for building intelligent systems. Conventional CBR systems have been largely designed as automated problem-solvers for producing a solution to a given problem by adapting the solution to a similar, previously solved problem. Such systems have had limited success in real-world applications. More recently, there has been a search for new paradigms and directions for increasing the utility of CBR systems for decision support. This paper focuses on the synergism between the research areas of CBR and decision support systems (DSSs). A conceptual framework for DSSs is presented and used to develop a taxonomy of three different types of CBR systems: 1) conventional, 2) decision-aiding, and 3) stimulative. The major characteristics of each type of CBR system are explained with a particular focus on decision-aiding and stimulative CBR systems. The research implications of the evolution in the design of CBR systems from automation toward decision-aiding and stimulation are also explored.