Empowering Data Mining Sciences by Habitual Domains Theory, Part II: Reaching Wonderful Solutions

Moussa Larbani () and Po Lung Yu ()
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Moussa Larbani: Carleton University
Po Lung Yu: University of Kansas

Annals of Data Science, 2020, vol. 7, issue 4, No 1, 549-580

Abstract: Abstract In the Part I of this paper, we presented the main concept of the proposed comprehensive decision model based on Habitual Domains theory, the concept of wonderful solution for solving challenging decision problems that we called decision making in changeable spaces problem (DMCS). In this Part II of the paper, we complete the construction of the model and show that it is operational and effectively empowers DMs in facing challenges. For this purpose, we present the mental principles “7–8–9 principles” that can be used to restructure decision parameters so that new solutions or alternatives could emerge. Then we provide procedures for finding wonderful solutions as sequences of the 7–8–9 principles by solving optimization in changeable spaces (OCS) problems, a new paradigm in optimization. Finally, we present applications of the model to post data mining analysis and decision making. In fact, the proposed model can be used in any area involving decision making and knowledge discovery such as management, politics, health care, technology and research.

Keywords: Post data mining; Habitual domain; Competence set; Wonderful solution (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40745-020-00291-z

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