Causal Graph Miner

This node implements the first step of the Hybrid Miner to discover a causal graph from an event table. A causal graph consists of nodes representing activities and directed arcs connecting them. We distinguish three types of these arcs: (1) strong dependencies are represented by blue solid arcs (certain arcs); (2) weak dependencies are represented by red dotted arcs (uncertain arcs); (3) long-term dependencies are represented by orange solid arcs.

Options

Case ID

The column that contains the case/trace identifiers.

Activity

The column that contains the activity/event identifiers.

Timestamp

The column that contains the timestamps.

Minimal activity frequency

An activity will be included if it occurs in at least x% of cases; set to 0 to include all activities.

Minimal trace variant frequency

A trace variant will be included if it covers at least x% of cases; set to 0 to include all trace variants.

Strong causality threshold

Lower bound for a strong causality between two activities.

Weak causality threshold

Lower bound for a weak causality between two activities; >set to 100% to avoid uncertain edges.

Long-term dependency threshold

Lower bound for a strong long-term causality between two activities.

Causality weight threshold

High values mean more emphasis on the split and join behavior of activities; low values mean more emphasis on the detection of concurrency and loops.

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Workflows

• 00_Process_Mining_with_Community_NodesKNIME Hub
• Discovery of Hybrid Process ModelsKNIME Hub

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