Semantic-Based Process Mining: A Conceptual Model Analysis and Framework

Semantics has been a major challenge when applying the Process Mining (PM) technique to real-time business processes. In theory, efforts to bridge the semantic gap has spanned the advanced notion of Semantic-based Process Mining (SPM). The SPM devotes its methods to the idea of making use of existing semantic technologies to support the analysis of PM techniques. Technically, the semantic-based process mining is applied through acquisition and representation of abstract knowledge about the domain processes in question. To this effect, this paper demonstrates how semantically focused process modelling and reasoning methods are used to improve the outcomes of PM techniques from the syntactic to a more conceptual level. Also, the work systematically reviews the current tools and methods that are used to support the outcomes of the process mining, and to this end, propose an SPM-based framework that proves to be more intelligent with a higher level of semantic reasoning aptitudes. In other words, this work provides a process mining approach that uses information (semantics) about different activities that can be found in any given process to generate rules and patterns through the method for annotation, conceptual assertions, and reasoning. Moreover, this is done to determine how the various activities that make up the said processes depend on each other or are performed in reality. In turn, the method is applied to enrich the informative values of the resultant models.

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