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The Resource A primer on process mining : practical skills with Python and Graphviz, Diogo R. Ferreira, (electronic book)

A primer on process mining : practical skills with Python and Graphviz, Diogo R. Ferreira, (electronic book)

Label
A primer on process mining : practical skills with Python and Graphviz
Title
A primer on process mining
Title remainder
practical skills with Python and Graphviz
Statement of responsibility
Diogo R. Ferreira
Creator
Author
Subject
Language
eng
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."--
Member of
Assigning source
Provided by publisher
Cataloging source
N$T
http://library.link/vocab/creatorName
Ferreira, Diogo R
Dewey number
658.4/0380151135
Index
no index present
LC call number
HF5548.2
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/subjectName
  • Business
  • Python (Computer program language)
  • Graphic methods
  • Computer graphics
Label
A primer on process mining : practical skills with Python and Graphviz, Diogo R. Ferreira, (electronic book)
Instantiates
Publication
Copyright
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
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
Dimensions
unknown
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9783319564265
Media category
computer
Media MARC source
rdamedia
Media type code
c
Reformatting quality
preservation
Sound
unknown sound
Specific material designation
remote
System control number
ocn990777950
Label
A primer on process mining : practical skills with Python and Graphviz, Diogo R. Ferreira, (electronic book)
Publication
Copyright
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
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
Dimensions
unknown
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9783319564265
Media category
computer
Media MARC source
rdamedia
Media type code
c
Reformatting quality
preservation
Sound
unknown sound
Specific material designation
remote
System control number
ocn990777950

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