A primer on process mining : practical skills with Python and Graphviz

"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...

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Bibliographic Details
Main Author Ferreira, Diogo R. (Author)
Format Electronic eBook
LanguageEnglish
Published Cham, Switzerland : Springer, [2017]
SeriesSpringerBriefs in information systems,
Subjects
Business > Data processing.
Python (Computer program language)
Graphic methods > Data processing.
Computer graphics.
elektronické knihy
electronic books
Online AccessFull text
ISBN9783319564272
9783319564265
ISSN2192-4929
Physical Description1 online resource

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Table of Contents:
  • 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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