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--- didattica:magistrale:pm:ay_1819:main [2018/10/25 09:10]
mescal [News]
+++ didattica:magistrale:pm:ay_1819:main [2020/09/17 16:55] (current)
@@ Line 3: / Line 3: @@
 ===== News =====
 <WRAP center round important 95%>
+  * <wrap em>**January 14th, 2019**</wrap>: On Thursday January 17th there will be no lesson
   * <wrap em>**October 25th, 2018**</wrap>: Dear student due to an unforeseen engagement I cannot deliver today's lesson.
   * October 2nd, 2018: Next lesson will be delivered on October 4th
@@ Line 46: / Line 47: @@
   * 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, Inductive Miner, Heuristic Miner 6.0, Split Miner (SM), and ILP Miner.
+  * 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.
@@ Line 60: / Line 61: @@
   * {{ :didattica:magistrale:pm:ay_1819:02_modeling.pdf |Formal Modeling of Processes}}
   * {{ :didattica:magistrale:pm:ay_1819:03_datamining.pdf |Data Mining - a short introduction}}
+  * {{ :didattica:magistrale:pm:ay_1819:gettingdata.pdf |Getting Data}}
+  * {{ :didattica:magistrale:pm:ay_1819:processdiscoveryanintroduction.pdf |Process Discovery an Introduction}}
+  * {{ :didattica:magistrale:pm:ay_1819:processdiscoveryanintroduction.pdf |Alpha Algorithm: A Process Discovery Algorithm}}
+  * {{ :didattica:magistrale:pm:ay_1819:processdiscoveryintroduction.pdf |Alpha Algorithm: Limitation}}
+  *  {{ :didattica:magistrale:pm:ay_1819:advancedprocessdiscoverytechniques.pdf |Quality, Heuristic and Genetic mining}}
+  * {{ :didattica:magistrale:pm:ay_1819:simonelli.pdf |Mining Experience}} ({{ :didattica:magistrale:pm:ay_1819:final_version_published.pdf |comparison}}) ({{ :didattica:magistrale:pm:ay_1819:bustech_2017_1_30_90020.pdf |methodology}})
+  * {{ :didattica:magistrale:pm:ay_1819:04_conformance.pdf |Conformance Checking}}
+  * {{ :didattica:magistrale:pm:ay_1819:05_additional.pdf |Mining Additional Perspectives}}
 ** Streaming **
   * October 8th, 2019
+  * [[https://unicam.webex.com/unicam/ldr.php?RCID=fe2bfba5c2586a1fb53df3f6df3967d3|January 7th, 2019]]
+  * [[https://unicam.webex.com/unicam/ldr.php?RCID=6b05f179855dc44ac9c7db863fcfc483|January 14th, 2019]]
+  * [[https://unicam.webex.com/unicam/ldr.php?RCID=04a7a61b1160c7f5e88c3c73e4573688|January 21st, 2019]]
 **Reference book:**
-  * Process Mining: Data Science in Action by W.M.P. van der Aalst, Springer Verlag, 2016 (ISBN 978-3-662-49850-7).
+  * 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:**
@@ Line 77: / Line 94: @@
 ===== Exams =====
 <WRAP box round center 95%>
+**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