Multi-phase Process Mining:
Building Instance Graphs
Jason Ree
3/31/11
School of Technology Management
UNIST
Introduction: Instance Graphs

Instance Graph
◦ Corresponds to a specific class of Petri nets
known as marked graphs, T-systems or partially
ordered runs
◦ An abstraction of the instance onto instance
Event-driven Process Chains (EPCs)
 Instance EPC
 Describes the control-flow of a case (i.e. a single process
instance)
 Provides a graphical representation describing the causal
relations
1.1 Process Instance

T
T+
σ

case 1
task S
case 1
task A
case 1
task B
In other words,
◦ Process Instance of length n: σ = t1t2 … tn ∈ T+ , where ti are tasks
◦ W ∈ T+  N denotes a bag (multiset of process instances)
◦ W(σ): the number of times a process instance of the form σ appears in the log
1.2 Instance Domain

Instance Net: a model of one instance

Since events that appear multiple times in a process instance have to be
duplicated in an instance net, we define an instance domain to be used as a
basis for generating instance nets


In an instance net, the instance σ is extended with some
ordering relation
to reflect some causal relation.
1.3 Instance Net


Also
◦ Since the set of entries is given as a log, and an instance mapping can be inferred for each
instance based on textual properties, only the ordering relation based on the given log needs
to be defined.

In other words,
◦ An instance net is defined only as a set of entries from the log and an ordering on that set
◦ Instance nets require
 1. sequence of events σ ∈ T+ as they appear in a specific instance
 2. ordering
on the domain of σ is required
Instance Net (σ,
)
2.1 Causal Ordering


Example
T = {S, A, B}

Causal ordering inferred on T
◦ S w A
◦ S w B
2.2 Instance Ordering


Example
◦ where case 1 = σ1 and case 2 = σ2
◦ σ1 = SAB and D σ1 = {1,2,3}
◦ Using the causal relation  the relation
Instance Net (σ,
is inferred such that 1
)
2 and 1
3
2.3 Instance Graph


In other words,
◦ An instance graph is a graph where each node represents one log entry of a specific
instance and can be used as a basis to generate models in a particular language
◦ Also it is a graph that typically describes an execution path of some process model, as well as
causal relations between tasks
3.1 Instance Event-driven Process
Chains (Instance EPCs)


Note:
◦
◦
An instance EPC doesn’t contain any connectors other than AND-split and AND-joins connectors
There is exactly one initial event and one final event
3.2 Generating Instance EPCs from
Instance Graphs

3.2 Generating Instance EPCs from
Instance Graphs
4.1 Example of Multi-Phase Process
Mining Using ProM
1.
Open Log data using ProM
4.1 Example of Multi-Phase Process
Mining Using ProM
Select Multi-Phase Macro Plugin
2.
◦
Mining > Multi-phase Macro Plugin
4.1 Example of Multi-Phase Process
Mining Using ProM
3.
Configure Options as needed for
analysis
4.1 Example of Multi-Phase Process
Mining Using ProM
4.
Visualization and Analysis of Event Log
Data
5. Example

1. Process Log

2. Finding Causal Relations
◦ {SA, AB, AC, AD, AE, BF, DH, EH,
FG, CG, HG, GT}
5. Example

3. Creation of Instance Graph
◦ 1) Instance ordering from Causal Relations
 0 1, 1 2, 2 3, 3 4, 4 8, 8 9, 2 5, 5 8, 2 6, 6 7, 7 8, 8 9, 9 10
◦ 2) Drawing Instance Graph from Instance Ordering
5. Example

4. Conversion of Instance Graph into Instance EPC
Thank you!

Questions?