Enhancing Business Decision Making Through Actionable Knowledge Discovery Using an Hybridized MCDM Mode

Ikuvwerha, Lucky and Amoo, Taiwo and Odumuyiwa, Victor and Oladipupo, O. O. (2020) Enhancing Business Decision Making Through Actionable Knowledge Discovery Using an Hybridized MCDM Mode. T Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. pp. 261-272.

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Abstract

Abstract. In recent years, with the increase in the usage of internet-enabled electronic devices and information systems, the upsurge and availability of volumes of high dimensional data have become one of the sources of high business value. The need for businesses to make informed decisions by lever�aging on the patterns from the multi-dimensional data have become paramount. However, the major issue is whether or not the patterns can optimize business decision making process to increase profit. Hence, there is need for actionable knowledge discovery (AKD). Therefore, this paper proposed an hybridized interval type-2 fuzzy Multi Criteria Decision Making (MCDM) model for evaluating patterns based on three subjective interestingness measure which are unexpectedness, actionability and novelty. The interval type-2 Fuzzy Analytical Hierarchy Process (AHP) was employed to weigh the patterns and Compen�satory AND approach was utilized for ranking the patterns using the three subjective interestingness measures. The proposed model depicts its applica�bility in identifying and ranking the patterns which are more relevant for enhancing business decision making.

Item Type:	Article
Subjects:	H Social Sciences > H Social Sciences (General) Q Science > Q Science (General)
Divisions:	Faculty of Law, Arts and Social Sciences > School of Social Sciences
Depositing User:	Dr ibukun Afolabi
Date Deposited:	18 Jun 2021 11:33
Last Modified:	18 Jun 2021 11:33
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/14717

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