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Soft Conformance Model Miner

Dependency

To use these algorithms in your Java Maven project it is necessary to include, in the pom.xml file, the dependency:

<dependency>
    <groupId>com.github.beamline</groupId>
    <artifactId>soft-conformance</artifactId>
    <version>master-SNAPSHOT</version>
</dependency>
See the introduction page for further instructions.

Usage

This miner can be used to extract a model to be used with the Soft Conformance technique. These models are not necessarily referring to the control-flow (e.g., they can be based on the social network of handover of work).

This miner extracts just a dependency map leveraging the directly follows relations observed in the stream. Once a XesSource is available, the miner can be configured and used as follows:

PDFAMiner miner = new PDFAMiner();
miner.setModelRefreshRate(1); // configure how ofter the mining algorithm should emit a new model

StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env
    .addSource(new StringTestSource("AABC", "ABC", "ABC", "ABC"))
    .keyBy(BEvent::getProcessName)
    .flatMap(miner)
    .addSink(new SinkFunction<PDFA>(){
        public void invoke(PDFA value, Context context) throws Exception {
            PDFAVisualizer.getDot(value).exportToSvg(new File("output.svg"));
        };
    });
env.execute();

This code will produce the following model:

G edf5adbb8-1495-49f7-bf4d-dae11812ecf2 A edf5adbb8-1495-49f7-bf4d-dae11812ecf2->edf5adbb8-1495-49f7-bf4d-dae11812ecf2 0.27 eab3fce2a-df45-43e8-9b62-89ce28ff3320 B edf5adbb8-1495-49f7-bf4d-dae11812ecf2->eab3fce2a-df45-43e8-9b62-89ce28ff3320 0.57 ea8b69327-9b41-4ca2-90b3-b6c8a50b04d4 C edf5adbb8-1495-49f7-bf4d-dae11812ecf2->ea8b69327-9b41-4ca2-90b3-b6c8a50b04d4 0.17 eab3fce2a-df45-43e8-9b62-89ce28ff3320->edf5adbb8-1495-49f7-bf4d-dae11812ecf2 0.17 eab3fce2a-df45-43e8-9b62-89ce28ff3320->eab3fce2a-df45-43e8-9b62-89ce28ff3320 0.17 eab3fce2a-df45-43e8-9b62-89ce28ff3320->ea8b69327-9b41-4ca2-90b3-b6c8a50b04d4 0.67 ea8b69327-9b41-4ca2-90b3-b6c8a50b04d4->edf5adbb8-1495-49f7-bf4d-dae11812ecf2 0.17 ea8b69327-9b41-4ca2-90b3-b6c8a50b04d4->eab3fce2a-df45-43e8-9b62-89ce28ff3320 0.17 ea8b69327-9b41-4ca2-90b3-b6c8a50b04d4->ea8b69327-9b41-4ca2-90b3-b6c8a50b04d4 0.17

Scientific literature

The techniques implemented in this package are described in: