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Multi-phase Process Mining: Building Instance Graphs

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

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Multi-phase Process Mining: Building Instance Graphs

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  1. Multi-phase Process Mining:Building Instance Graphs Jason Ree 3/31/11 School of Technology Management UNIST

  2. 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

  3. 1.1 Process Instance • 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 T+ σ T

  4. 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.

  5. 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, )

  6. 2.1 Causal Ordering • Example • Causal ordering inferred on T • S wA • S w B T = {S, A, B}

  7. 2.2 Instance Ordering • Example • where case 1 = σ1 and case 2 = σ2 • σ1 = SAB and Dσ1 = {1,2,3} • Using the causal relation  the relation is inferred such that 1 2 and 1 3 Instance Net (σ, )

  8. 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

  9. 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

  10. 3.2 Generating Instance EPCs from Instance Graphs

  11. 3.2 Generating Instance EPCs from Instance Graphs

  12. Thank you! • Questions?

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