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A Knowledge-Based Software Life-Cycle Framework for the Incorporation of Multicriteria Analysis in Intelligent User Interfaces

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2 Author(s)

Decision-making theories aiming at solving decision problems that involve multiple criteria have often been incorporated in knowledge-based systems for the improvement of these systems' reasoning process. However, multicriteria analysis has not been used adequately in intelligent user interfaces, even though user-computer interaction is, by nature, multicriteria-based. The actual process of incorporating multicriteria analysis into an intelligent user interface is neither clearly defined nor adequately described in the literature. It involves many experimental studies throughout the software life-cycle. Moreover, each multicriteria decision-making theory requires different kinds of experiments for the criteria to be determined and then for the proper respective weight of each criterion to be specified. In our research, we address the complex issue of developing intelligent user interfaces that are based on multicriteria decision-making theories. In particular, we present and discuss a software life-cycle framework that is appropriate for the development of such user interfaces. The life-cycle framework is called MBIUI. Given the fact, that very little has been reported in the literature about the required experimental studies, their participants and the appropriate life-cycle phase during which the experimental studies should take place, MBIUI provides useful insight for future developments of intelligent user interfaces that incorporate multicriteria theories. One significant advantage of MBIUI is that it provides a unifying life-cycle framework that may be used for the application of many different multicriteria decision-making theories. In the paper, we discuss the incorporation features of four distinct multicriteria theories: TOPSIS, SAW, MAUT, and DEA. Furthermore, we give detailed specifications of the experiments that should take place and reveal their similarities and differences with respect to the theories

Published in:

IEEE Transactions on Knowledge and Data Engineering  (Volume:18 ,  Issue: 9 )