Inductive miner belongs to a class of algorithms used in process discovery. Various algorithms proposed previously give process models of slightly different type from the same input. The quality of the output model depends on the soundness of the model. A number of techniques such as alpha miner, genetic miner, work on the basis of converting an event log into a workflow model, however, they do not produce models that are sound all the time. Inductive miner relies on building a directly follows graph from event log and using this graph to detect various process relations.
Definitions A directly follows graph is a directed graph that connects an activity A to another activity B if and only if activity B occurs chronologically right after activity A for any given case in the respective event log. A directly follows graph is represented mathematically by:
G ( L ) = ( A L ∪ { ▸ , ◼ } , → L , A L s , A L e ) {\displaystyle G(L)=(A_{L}\cup \{\blacktriangleright ,\blacksquare \},\rightarrow _{L},A_{L}^{s},A_{L}^{e})}
Where
A L = N o d e s (activities in the log) , ▸ = virtual start node , ◼ = virtual end node {\displaystyle A_{L}=Nodes{\text{(activities in the log)}},\blacktriangleright ={\text{virtual start node}},\blacksquare ={\text{virtual end node}}}
→ L = e d g e s {\displaystyle \rightarrow _{L}=edges} (directly follows relation) If some activity a is ever the first activity, then
( ▸ , a ) ∈ → L {\displaystyle (\blacktriangleright ,a)\in \rightarrow _{L}} . Similarly, if some activity a is ever the last activity, then ( a , ◼ ) ∈ → L {\displaystyle (a,\blacksquare )\in \rightarrow _{L}}
A L s = { a ∈ A L | ( ▸ , a ) ∈ → L } {\displaystyle A_{L}^{s}=\{a\in A_{L}\ |\ (\blacktriangleright ,a)\in \rightarrow _{L}\}} the set of all "starting nodes"
A L e = { a ∈ A L | ( a , ◼ ) ∈ → L } {\displaystyle A_{L}^{e}=\{a\in A_{L}\ |\ (a,\blacksquare )\in \rightarrow _{L}\}} the set of all "ending nodes" The inductive miner technique relies on the detection of various cuts on the directly follows graph created using the event log. The core idea behind inductive miner lies in the unique methodology of discovering various divisions of the arcs in the directly follows graph, and using the smaller components after division to represent the execution sequence of the activities. The inductive miner algorithm uses the directly follows graph to detect one of the following cuts.
Exclusive OR cut: The exclusive OR cut groups the activities such that the activities belonging to different groups have no relations between them.
( × , A 1 , . . . , A n ) {\displaystyle (\times ,A_{1},...,A_{n})} is an exclusive OR cut iff: ∀ i , j ∈ { 1 , . . , n } ( ∀ a ∈ A i , b ∈ A j ( i ≠ j ⇒ ¬ ( a → L b ) ) ) {\displaystyle \forall i,j\in \{1,..,n\}(\forall a\in A_{i},b\in A_{j}(i\neq j\Rightarrow \neg (a\rightarrow _{L}b)))}
Sequence cut: The sequence cut groups activities such that activities between them have a directly follows relation from previous group to next group but not the other way around.
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