Experimental Setup and Case Study Example

Experimental Setup and Case Study Example

Copyright: © 2020 |Pages: 13
DOI: 10.4018/978-1-7998-2668-2.ch006
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Abstract

This chapter represents as a practical follow-up or implementation of the main components of the SPMaAF described in Chapter 5. In the experimental setup, the chapter demonstrates by using the case study of the learning process: the development and application of the semantic-based process mining. Essentially, the chapter looks at how the proposed semantic-based process mining and analysis framework (SPMaAF) is applied to answer real-time questions about any given process domain, as well as the classification of the individual process instances or elements that constitutes process models. This includes the semantic representations and modelling of the learning process in order to allow for an abstraction analysis of the resultant models. The chapter finalizes with a conceptual description of the resultant semantic fuzzy mining approach which is discussed in detail in the next chapter.
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Semantic Representations And Modelling Of The Learning Process Domain

In this section, the work applies semantic representations to determine the different patterns or behaviours that describes/distinguishes certain entities within the learning knowledge base from another. Thus, the method is used to recognize (determine) what attributes/paths the learners (i.e. process instances) have in common or follow, or what attributes distinguish the successful learners from the uncomplete ones.

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