Fuzzy ontology-based approach for the requirements query imprecision assessment in data warehouse design process near negative fuzzy operator
Автор: Larbi Abdelmadjid, Malki Mimoun, Boukhalfa Kamel
Журнал: International Journal of Information Technology and Computer Science @ijitcs
Статья в выпуске: 2 Vol. 10, 2018 года.
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The vagueness in decision-making may be due to ambiguity in the decisional requirements expression. Therefore, in the literature dealing with vagueness in decision systems, studies were concentrated on data vagueness and not on decision requirements. In order to evaluate the expression in decision-making requirements and in order to improve the data warehouses design quality, this paper presents a rigorous fuzzy ontology-based solution. Based on the latest Zadeh theory “Ref. [1]”, Authors in “Ref. [2.3]”, propose a solution consisting in using ontologies to provide "an understanding of how the meaning of a proposal can be composed of the meaning of its constituents. One of the limitations of this solution is the fuzziness presence only at the adjective sentence. In some sense, our proposal can be seen as a continuation of that work. We limit our study, in this paper to the “Near negative” operator case. To the best of our knowledge, this case has not been addressed yet in the data warehouse context.
Data warehouses design, requirement expression, decisional system, fuzzy ontology, GLMR Model, imprecision, OLAP Analysis, NEAR- Operator
Короткий адрес: https://sciup.org/15016233
IDR: 15016233 | DOI: 10.5815/ijitcs.2018.02.03
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