/faculteit technologie management 1 Process Mining: Control-Flow Mining Algorithms Ana Karla Alves de Medeiros Ana Karla Alves de Medeiros Eindhoven University of Technology Department of Information Systems

/faculteit technologie management 2 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 3 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 4 Process Mining 1.Register at hospital 2.Talk to doctor 3.Take blood test 4.Take X-ray 5.Get results 6.Talk to doctor 7.Go home 1.Register at hospital 2.Talk to doctor 3.Undergo surgery 4.Take medicines 5.Take blood sample 6.Talk to doctor 7.Go home 1.Register at hospital 2.Talk to doctor 3.Undergo surgery 4.Take medicines 5.Take blood sample 6.Talk to doctor 7.Go homeEventLogs 1.Register at hospital 2.Talk to doctor 3.Undergo surgery 4.Take medicines 5.Take blood sample 6.Talk to doctor 7.Go home 1.Register at hospital 2.Talk to doctor 3.Undergo surgery 4.Take medicines 5.Take blood sample 6.Talk to doctor 7.Go home 1.Register at hospital 2.Talk to doctor 3.Undergo surgery 4.Take medicines 5.Take blood sample 6.Talk to doctor 7.Go home

/faculteit technologie management 5 Process Mining Performance Analysis Process Model Organizational Model Social Network EventLog MiningTechniques Auditing/Security MinedModels

/faculteit technologie management 6 Event Logs are Everywhere! aaaaaa aaaaaa Machines, Municipalities, Airports, Internet, Hospitals, etc.

/faculteit technologie management 7 Tools ProM 4.2 ProMimport Free tools!

/faculteit technologie management 8 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 9 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 10 Types of Algorithms

/faculteit technologie management 11 Process Model Organizational Model Social Network Types of Algorithms

/faculteit technologie management 12 Auditing/Security Compliance Process Model Types of Algorithms

/faculteit technologie management 13 Bottlenecks/ Business Rules Process Model Performance Analysis Types of Algorithms

/faculteit technologie management 14 Process Mining EventLog Discovery Techniques: Control-Flow Mining MinedModel 1.Start 2.Get Ready 3.Travel by Train 4.Beta Event Starts 5.Visit Brewery 6.Have Dinner 7.Go Home 8.Travel by Train 1.Start 2.Get Ready 3.Travel by Train 4.Beta Event Starts 5.Give a Talk 6.Visit Brewery 7.Have Dinner 8.Go Home 9.Travel by Train 1.Start 2.Get Ready 3.Travel by Car 4.Beta Event Starts 5.Give a Talk 6.Visit Brewery 7.Have Dinner 8.Go Home 9.Pay Parking 10.Travel by Car 1.Start 2.Get Ready 3.Travel by Car 4.Conference Starts 5.Join Reception 6.Have Dinner 7.Go Home 8.Pay Parking 9.Travel by Car 10.End Start Get Ready Travel by Train Train Travel by Car Car Conference Starts Give a Talk Join Reception Have Dinner Go Home Travel by Train Train Travel by Car Car PayParking End

/faculteit technologie management 15 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 16 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 17 Common Constructs Sequence Splits Joins Loops Non-Free Choice Invisible Tasks Duplicate Tasks PayParking GetReady Travel by Train Train Travel by Car Car Defense Starts Give a Talk Ask Question Defense Ends Go Home Travel by Train Train Travel by Car Car Have Drinks

/faculteit technologie management 18 Common Constructs Sequence Splits Joins Loops Non-Free Choice Invisible Tasks Duplicate Tasks PayParking GetReady Travel by Train Train Travel by Car Car Defense Starts Give a Talk Ask Question Defense Ends Go Home Travel by Train Train Travel by Car Car Have Drinks + noise in logs!

/faculteit technologie management 19 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 20 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 21 Event Log: Mining XML (MXML) The notion of which tasks belong to a same instance is crucial for applying process mining techniques!

/faculteit technologie management 22 Event Log: Mining XML (MXML)

/faculteit technologie management 23 Event Log: Mining XML (MXML) Compulsory fields!

/faculteit technologie management 24 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 25 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 26 α-algorithm 1.Read a log 2.Get the set of tasks 3.Infer the ordering relations 4.Build the net based on inferred relations 5.Output the net Core Step!

/faculteit technologie management 27 Direct succession: x>y iff for some case x is directly followed by y. Causality: x  y iff x>y and not y>x. Parallel: x||y iff x>y and y>x Unrelated: x#y iff not x>y and not y>x. case 1 : task A case 2 : task A case 3 : task A case 3 : task B case 1 : task B case 1 : task C case 2 : task C case 4 : task A case 2 : task B... A>BA>CB>CB>DC>BC>DE>F ABABACACBDBDCDCDEFEFABABACACBDBDCDCDEFEF B||CC||BABCDACBDEF α-algorithm - Ordering Relations >, ,||,#

/faculteit technologie management 28 Let W be a workflow log over T.  (W) is defined as follows. 1.T W = { t  T     W t   }, 2.T I = { t  T     W t = first(  ) }, 3.T O = { t  T     W t = last(  ) }, 4.X W = { (A,B)  A  T W  B  T W   a  A  b  B a  W b   a1,a2  A a 1 # W a 2   b1,b2  B b 1 # W b 2 }, 5.Y W = { (A,B)  X   (A,B)  X A  A  B  B  (A,B) = (A,B) }, 6.P W = { p (A,B)  (A,B)  Y W }  {i W,o W }, 7.F W = { (a,p (A,B) )  (A,B)  Y W  a  A }  { (p (A,B),b)  (A,B)  Y W  b  B }  { (i W,t)  t  T I }  { (t,o W )  t  T O }, and  (W) = (P W,T W,F W ). α-algorithm - Formalization

/faculteit technologie management 29ABCDACBDEF ABABACACBDBDCDCDEFEFABABACACBDBDCDCDEFEF B||CC||B α-algorithm - Insight

/faculteit technologie management 30 If log is complete with respect to relation >, it can be used to mine SWF-net without short loops Structured Workflow Nets (SWF-nets) have no implicit places and the following two constructs cannot be used: α-algorithm – Log properties + target nets

/faculteit technologie management 31 One-length Two-length B>B and not B>B implies BB (impossible!) A>B and B>A implies A||B and B||A instead of AB and BA α-algorithm – No short loops Why no short loops?

/faculteit technologie management 32 No invisible tasks, non-free-choice or duplicate tasks No noisy logs α-algorithm – Common Constructs Why no duplicate tasks? Why not invible tasks? Why noise- free logs?

/faculteit technologie management 33 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Algorithm Fuzzy Miner

/faculteit technologie management 34 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Algorithm Fuzzy Miner

/faculteit technologie management 35 Heuristics Miner 1.Read a log 2.Get the set of tasks 3.Infer the ordering relations based on their frequencies 4.Build the net based on inferred relations 5.Output the net

/faculteit technologie management 36 Heuristics Miner Insight: The more frequently a task A directly follows another task B, and the less frequently the opposite occurs, the higher the probability that A causally follows B!

/faculteit technologie management 37 No non-free-choice or duplicate tasks Robust to invisible tasks and noisy logs α-algorithm – Common Constructs Why no non-free- choice? Why no guarantee whole net will be correct?

/faculteit technologie management 38 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 39 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 40 Genetic Process Mining (GPM) Genetic Algorithms + Process Mining Genetic Algorithms –Search technique that mimics the process of evolution in biological systems Advantages –Tackle all common structural constructs –Robust to noise Disadvantages –Computational Time

/faculteit technologie management 41 Genetic Process Mining (GPM) Algorithm: Internal Representation Fitness Measure Genetic Operators

/faculteit technologie management 42 GPM – Fitness Measure Start Get Ready Travel by Train Train Travel by Car Car Conference Starts Give a Talk Visit Brewery Have Dinner Go Home Travel by Train Train Travel by Car Car PayParking End Guides the search!

/faculteit technologie management 43 GPM – Fitness Measure

/faculteit technologie management 44 GPM – Fitness Measure Start Get Ready Travel by Car Car Conference Starts Give a Talk Visit Brewery Have Dinner Go Home PayParking End Travel by Train Train Punish for the amount of enabled tasks during the parsing! Overgeneral solution

/faculteit technologie management 45 GPM – Fitness Measure Start Get Ready Travel by Car Conference Starts Give a Talk Visit Brewery Have Dinner Go Home Travel by Train Travel by Car Pay Parking End Travel by Train Punish for the amount of duplicate tasks with common input/output tasks! Overspecific solution

/faculteit technologie management 46 GPM – DGA ProM Plug-in Why does the GA Miner takes so much time? How could we improve its running time without changing the code?

/faculteit technologie management 47 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 48 Process Mining Short Recap Types of Process Mining Algorithms Common Constructs Input Format α-algorithm Heuristics Miner Genetic Miner Fuzzy Miner

/faculteit technologie management 49 Fuzzy Miner - Motivation Mine less structured processes!

/faculteit technologie management 50 Fuzzy Miner - Motivation

/faculteit technologie management 51 Fuzzy Miner

/faculteit technologie management 52 Fuzzy Miner No “Ask Question” or “Give Talk”! All details! Abstracting even more from details!

/faculteit technologie management 53 Conclusions The notion of a process instance is crucial! Ordering of tasks is the basic information Frequencies are important to handle noise Local approaches – α-algorithm, Heuristics Miner Global approaches – Genetic Miner and Fuzzy Miner