Visual-aided ontology-based ranking on multidimensional data: a case study in academia
Data Technologies and Applications
ISSN: 2514-9288
Article publication date: 27 July 2018
Issue publication date: 20 August 2018
Abstract
Purpose
The purpose of this paper is to introduce a novel framework for visual-aided ontology-based multidimensional ranking and to demonstrate a case study in the academic domain.
Design/methodology/approach
The paper presents a method for adapting semantic web technologies on multiple criteria decision-making algorithms to endow to them dynamic characteristics. It also showcases the enhancement of the decision-making process by visual analytics.
Findings
The semantic enhanced ranking method enables the reproducibility and transparency of ranking results, while the visual representation of this information further benefits decision makers into making well-informed and insightful deductions about the problem.
Research limitations/implications
This approach is suitable for application domains that are ranked on the basis of multiple criteria.
Originality/value
The discussed approach provides a dynamic ranking methodology, instead of focusing only on one application field, or one multiple criteria decision-making method. It proposes a framework that allows integration of multidimensional, domain-specific information and produces complex ranking results in both textual and visual form.
Keywords
Citation
Triperina, E., Bardis, G., Sgouropoulou, C., Xydas, I., Terraz, O. and Miaoulis, G. (2018), "Visual-aided ontology-based ranking on multidimensional data: a case study in academia", Data Technologies and Applications, Vol. 52 No. 3, pp. 366-383. https://doi.org/10.1108/DTA-03-2017-0014
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited