Semantic-Based Process Mining Technique for Annotation and Modelling of Domain Processes

Article


Okoye, K., Islam, S., Naeem, U. and Sharif, S. 2020. Semantic-Based Process Mining Technique for Annotation and Modelling of Domain Processes. International Journal of Innovative Computing, Information and Control. 16 (3), pp. 899-921.
AuthorsOkoye, K., Islam, S., Naeem, U. and Sharif, S.
Abstract

Semantic technologies aim to represent information or models in formatsthat are not just machine-readable but also machine-understandable. To this effect, thispaper shows how the semantic concepts can be layered on top of the derived models toprovide a more contextual analysis of the models through the conceptualization method.Technically, the method involves augmentation of informative value of the resulting mod-els by semantically annotating the process elements with concepts that they represent inreal-time settings, and then linking them to an ontology in order to allow for a moreabstract analysis of the extracted logs or models. The work illustrates the method usingthe case study of a learning process domain. Consequently, the results show that a systemwhich is formally encoded with semantic labelling (annotation), semantic representation(ontology) and semantic reasoning (reasoner) has the capacity to lift the process miningand analysis from the syntactic to a more conceptual level.

JournalInternational Journal of Innovative Computing, Information and Control
Journal citation16 (3), pp. 899-921
ISSN1349-418X
Year2020
PublisherICIC International
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Anyone
Digital Object Identifier (DOI)doi:10.24507/ijicic.16.03.899
Web address (URL)https://doi.org/10.24507/ijicic.16.03.899
Publication dates
OnlineJun 2020
Publication process dates
Deposited25 Jun 2020
Accepted13 Jan 2020
Copyright holder© 2020 ICIC International
Copyright informationAll Rights Reserved.
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