A primer on process mining : practical skills with Python and Graphviz / Diogo R. Ferreira.
Ferreira, Diogo R., author.
2017
HF5548.2
Available Online

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Title A primer on process mining : practical skills with Python and Graphviz / Diogo R. Ferreira.
Author Ferreira, Diogo R., author.
ISBN 9783319564272 (electronic book)
3319564277 (electronic book)
9783319564265
3319564269
Published Cham, Switzerland : Springer, [2017]
Copyright ©2017
Language English
Description 1 online resource.
Call Number HF5548.2
Dewey Decimal Classification 658.4/0380151135
Summary "The main goal of this book is to explain the core ideas of process mining, and to demonstrate how they can be implemented using just some basic tools that are available to any computer scientist or data scientist. It describes how to analyze event logs in order to discover the behavior of real-world business processes. The end result can often be visualized as a graph, and the book explains how to use Python and Graphviz to render these graphs intuitively. Overall, it enables the reader to implement process mining techniques on his or her own, independently of any specific process mining tool. An introduction to two popular process mining tools, namely Disco and ProM, is also provided. The book will be especially valuable for self-study or as a precursor to a more advanced text. Practitioners and students will be able to follow along on their own, even if they have no prior knowledge of the topic."-- Provided by publisher.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (viewed June 26, 2017).
Available in Other Form Print version: 3319564269
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Preface; Contents; 1 Event Logs; 1.1 Process Model vs. Process Instances; 1.2 Task Allocation; 1.3 Identifying the Process Instances; 1.4 Recording Events in an Event Log; 1.5 Event Logs in CSV Format; 1.6 Reading an Event Log with Python; 1.7 Sorting an Event Log with Python; 1.8 Reading the Event Log as a Dictionary; 1.9 Summary; 2 Control-Flow Perspective; 2.1 The Transition Matrix; 2.2 The Control-Flow Algorithm; 2.3 Implementation in Python; 2.4 Introducing Graphviz; 2.5 Using PyGraphviz; 2.6 Edge Thickness; 2.7 Activity Counts; 2.8 Node Coloring; 2.9 Summary

3 Organizational Perspective3.1 Handover of Work; 3.2 Implementing Handover of Work; 3.3 Working Together; 3.4 Implementing Working Together; 3.5 Undirected Graphs; 3.6 Edge Thickness; 3.7 Users and Activities; 3.8 Work Distribution; 3.9 Summary; 4 Performance Perspective; 4.1 Dates and Times in Python; 4.2 Parsing the Timestamps; 4.3 Average Timestamp Difference; 4.4 Drawing the Graph; 4.5 Analyzing the Timeline of Events; 4.6 Plotting the Dotted Chart; 4.7 Using Relative Time; 4.8 Activity Duration; 4.9 Summary; 5 Process Mining in Practice; 5.1 The BPI Challenge 2012

5.2 Understanding the XES Format5.3 Reading XES with Python; 5.4 Analyzing the Control-Flow Perspective; 5.5 Analyzing the Organizational Perspective; 5.6 Analyzing the Performance Perspective; 5.7 Process Mining with Disco; 5.8 Process Mining with ProM; 5.9 Conclusion; References

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