Process Mining


  • January 14th, 2019: On Thursday January 17th there will be no lesson
  • October 25th, 2018: Dear student due to an unforeseen engagement I cannot deliver today's lesson.
  • October 2nd, 2018: Next lesson will be delivered on October 4th

Teachers:

  • Andrea Polini, Barbara Re

ESSE3 Link

Lessons Scheduling:

  • 42 h - lecture and exercise sessions
  • Monday: 2:00 PM – 4:00 PM
  • Thursday: 2:00 PM – 4:00 PM

  • This course focuses on the the missing link between model-based process analysis and data-oriented analysis techniques
  • The course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains
  • The course explains various process discovery algorithms,
  • The course introduce conformance techniques to compare processes and event data
  • The course provides to students the opportunity to experiment with real tools
  • At the end of the course, the students will gain familiarity with process mining terminology, methodology and technologies
  • Be able to apply basic process discovery techniques to learn a process model from an event log
  • Be able to apply basic conformance checking techniques to compare event logs and process models
  • Have a good understanding of the data needed to start a process mining project
  • Be able to conduct process mining projects in a structured manner
  • Introduction to Process Mining and Data Mining. Data. Logs. Play-in, Play Out and Reply. Fundamentals of Process Modelling.
  • From Event Logs to Process Models. Getting Data. Process Discovery. Discovery Techniques an Introduction. Tools support an introduction: Apromore, Disco, and ProM.
  • Discovery Algorithms. Alfa, Heuristic, Genetic Miner.
  • Conformance Checking. Business Alignment and Auditing. Token Replay. Process Drift. Business Process Model and Instances. Business Process Life-Cycle. Classification of Business Process.

Project Based on 2018 Business Process Intelligence Challenge (BPIC) - https://www.win.tue.nl/bpi/doku.php?id=2018:challenge

Project Based Examination on the topics of the syllabus including project presentation

  1. Process Mining Challenge: (i) we will provide real data set, (ii) we will provide questions to be answered
  2. We expect that you can focus on a specific aspect of interest and analyze this aspect in great detail using any technique, method, algorithm, and tool
  3. We will judge based on: (i) the originality of the results, (ii) the validity of the claims, and (iii) the depth of the analysis of specific issues identified

Dates (https://didattica.unicam.it/Home.do)