didattica:magistrale:pm:ay

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:

ESSE3 Link

Lessons Scheduling:

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.

Classes Scheduling

Course Slides

Streaming

Reference book:

Process Mining: Data Science in Action by W.M.P. van der Aalst, Springer Verlag, 2016 (ISBN 978-3-662-49850-7). From chapter 1 to 9.

Tools:

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

Process Mining Challenge: (i) we will provide real data set, (ii) we will provide questions to be answered
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
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)

Process Mining