Title: Using advanced web ontology language properties for deriving novel and consistent association rules

Authors: Eliot Bytyçi; Lule Ahmedi

Addresses: University of Prishtina 'Hasan Prishtina', George Bush, No. 31, 10000, Prishtina, Republic of Kosovo ' University of Prishtina 'Hasan Prishtina', George Bush, No. 31, 10000, Prishtina, Republic of Kosovo

Abstract: Association rule mining has long been used to discover relationship between data. On the other hand, using ontology properties can lead to the discovery of new knowledge that can be combined with raw data to produce increasing number of association rules generated. The exploitation can also prevent the creation of additional, erroneous rules. Three domain ontologies are employed in the studies to support both assertions and determine which attributes are likely to have a greater impact on rules creation. Initial enrichment of ontologies with the same type of properties, is then followed by application of association rules algorithms to each ontology. Results are contrasted with those produced using association rules applied to raw data. The work's contribution can be divided into two categories: creating new rules and preventing the creation of new conflicting rules.

Keywords: association rule mining; ARM; ontology; web ontology language; OWL; advanced properties; semantic web.

DOI: 10.1504/IJBIDM.2023.134321

International Journal of Business Intelligence and Data Mining, 2023 Vol.23 No.4, pp.411 - 429

Accepted: 30 Aug 2022
Published online: 18 Oct 2023 *

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