Formulation of quantitative models has received considerable attention in DSS research. Formulation of decision models for complex decision problems exhibiting less structure, more imprecision and uncertainty is not adequately addressed. This paper presents a methodology for formulation of qualitative models to handle such problems. The methodology… (More)
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Decision support and knowledge management processes are interdependent activities in many organizations. In this paper, we propose an approach for integrating decision support and knowledge management processes using knowledge discovery techniques. Based on the proposed approach, an integrative framework is presented for building enterprise decision support… (More)
Knowing the kinds of modeling errors they are most likely to produce helps prepare novice analysts for developing quality conceptual models.
Assuring quality in capturing and representing the systems requirements is extremely important. This study is aimed at understanding errors frequently committed by novice systems analysts in developing domain models using the Unified Modeling Language (UML). Understanding of errors that affect the quality of resulting conceptual models and the relationships… (More)
Data mining is usually associated with centralized data mining systems. Here we present an approach to develop a data mining system in distributed environments. The main difficulty in this approach is the unrestricted sharing of information and dynamic integration of components. In this paper, we present a Web Service-based approach to solve these problems.… (More)