Kerry Lumi

Tartu

2013

* Predictive Analytics for Semi-structured CaseOriented Business Processes

Semi-structured business processes lifecycle is not fully driven by a formal process model

The execution of a semi-structuredprocess is not completely controlled by a central entity

Case oriented processes are an example of semi-structured business processes.

Semi-structured CaseOriented Business ProcessBusiness process management systems typically include restrictions such as rigid control flow and context tunneling

Automobile insurance claims handling scenario

The scenario has been simplified for the sake of achieving clarity in our experiments and results

Scenario

An ant-colony optimization (ACO) based algorithm was applied to create a probabilistic activity graph from traces, and use it to identify key decision points in a given process.

Using standard decision tree learning algorithm likelihood of different outcomes from the node can be correlated with the contents of documents accessed by the activity node.

Implementation

Results on an automobile insurance industry claims scenario indicate that this approach can be useful for predicting outcomes that immediately follow a given decision point, final outcomes, and intermediate outcomes that occur between immediate and final outcomes

Furthermore our experiments indicate that this approach can be useful for predicting outcomes of decisions in situations where not all the data values necessary to make a decision are available

This approach also demonstrates a way to identify decision points ina semi-structured process using a probabilistic graph without necessarily mining a process model to represent the process

Conclusion

Thank you!