Measuring the Impact of the Semantic-Based Process Mining Approach

This chapter looks at the extent to which the semantic-based process mining approach of this book supports the conceptual analysis of the events logs and resultant models. Qualitatively, the chapter leverages the use case study of the research learning process domain to determine how the proposed method support the discovery, monitoring, and enhancement of the real-time processes through the abstraction levels of analysis. Also, the chapter quantitatively assesses the level of accuracy of the classification process to predict behaviours of unobserved instances within the underlying knowledge base. Overall, the work looks at the implications of the semantic-based approach, validation of the classification results, and their influence compared to other existing benchmark techniques/algorithms used for process mining.

Proposed Algorithms and Formalizations

In this chapter, the work presents and describes the different algorithms that it proposes for ample implementation of the SPMaAF framework. The procedures outlined in the Algorithms 1, 2, and 3 illustrates the method that the work applies for developing the semantic-based process mining approach described in this book. Technically, the outlined procedures (i.e., Algorithms 1, 2, and 3) are aligned with the entire speculation of the work in this book, which are grounded on the three different phases or components of the SPMaAF Framework.

Method for Semantic Annotation and Lifting of Process Models

The work done in this chapter demonstrates how the main components of the SPMaAF framework and sets of algorithms described earlier in Chapters 3 and 4, respectively, fit and rely on each other in achieving the semantic enhancement of the discovered process models. This is done by representing the models discovered through the standard process mining techniques as a set of annotated terms that links to or references the concepts defined within ontologies. It permits the process analysts to formally represent and analyse the several information in the underlying knowledge-bases in a more efficient and yet accurate manner. Henceforth, the conceptualisation method or tactics is allied to semantic lifting of the process models.

State-of-the-Art Components, Tools, and Methods for Process Mining and Semantic Modelling

This chapter describes the state-of-the-art technologies, tools, and methods that are closely connected to the work done in this book. The chapter describes in detail the key components of the process mining and semantic modelling methods and the different technologies that enable the practical application of the techniques. In essence, the chapter explains the main tools and mechanisms that are applied in this book, ranging from the events log to the different tools that are applied for process mining, and the existing algorithms used to discover the process models and to support the interpretations and/or further analysis of the models at semantic levels.

Process Mining With Semantics

This chapter contains the application of the semantic process mining approach in real-time. This includes the series of analysis that were performed not only to show how the method is applied in different scenarios or settings for process mining purposes, but also how to technically apply the method for semantic process mining tasks. In the first section, the work shows how the authors practically apply the current tools that supports the process mining through its participation in the Process Discovery Contest organised by the IEEE CIS Task Force on Process Mining. In the second section, the chapter shows how it expounds the results and amalgamation of the two process mining techniques, namely fuzzy miner and business process modelling notation (BPMN) approach, in order to demonstrate the capability of the proposed semantic-based fuzzy miner being able to perform a more conceptual and accurate classification of the individual traces within the process or input models.

Experimental Setup and Case Study Example

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.

Main Component and Architecture of the Semantic-Based Process Mining and Analysis Framework (SPMaAF)

This chapter describes the proposed semantic-based process mining and analysis framework (SPMaAF) and the main components applied for integration and ample implementation of the method. Technically, the conceptual method of analysis and how the book has designed the framework is explained in detail. The chapter also shows that the quality augmentation of the derived process models is as a result of employing process mining techniques that encodes the envisaged system with three rudimentary building blocks, namely semantic labelling (annotation), semantic representation (ontology), and semantic reasoning (reasoner).

Preliminaries

This chapter looks at the relevant tools and technologies that are related/applicable to the process mining and semantic modelling techniques. Theoretically, the chapter describes some of the interrelated tools and area of topics covered by this book. In other words, the chapter introduces the background information that is essential for understanding the context and proposed method of this book. It starts by looking at the process mining term and the different types of its application when applied to solve real-time problems. Consequently, the chapter discusses the wider scope of the different semantic-aware methods that trails to provide valuable information or insights that can be utilized to support the real-time processing or decision-making purposes.