1 - 5 of 5 Chapters
[This chapter explains how event logs are generated by the execution of multiple instances of a business process. The kind of event logs that are used for process mining have a particular structure and can be stored in a text file. The chapter explains how to parse those files and read the event...
[This chapter explains how to derive a control-flow model for a business process, based on counting transitions between events. A simple control-flow algorithm is described together with its implementation in Python. The chapter also introduces Graphviz as a means to display the resulting model....
[This chapter describes the main techniques to analyze the interactions and collaborations between participants in a business process. These techniques consist in simple algorithms that are straightforward to implement in Python. The chapter also provides an introduction to the use of process...
[The performance perspective is concerned mainly with time. Examples of interesting time measurements are the average time it takes to perform an activity, the maximum time it takes for the process to reach a certain point, or the average end-to-end duration of each process instance.]
[Over the years, the process mining community has placed several real-world event logs in the public domain. Most of these event logs have been released in the scope of process mining competitions, where contestants could use any of the available techniques, or even develop new techniques, to...
Read and print from thousands of top scholarly journals.
Continue with Facebook
Sign up with Google
Log in with Microsoft
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Sign Up Log In
To subscribe to email alerts, please log in first, or sign up for a DeepDyve account if you don’t already have one.
To get new article updates from a journal on your personalized homepage, please log in first, or sign up for a DeepDyve account if you don’t already have one.