Workflow extraction for service operation using multiple unstructured trouble tickets

In current large scale networks, troubleshooting has become more complicated task due to the diversification in the causes of network failures. The increase in the operational costs has become a serious problem. Thus, manualization of the troubleshooting process also becomes important task though it is time-consuming. We propose a method that automatically extracts a workflow for troubleshooting using multiple trouble tickets. Our method extracts an operator's actions from free-format texts and aligns relative sentences between multiple trouble tickets. Finally, we show a novel approach to visualizing a workflow by mining conditional branches using clustering. We validated our method using real trouble ticket data captured from a network operation and showed that it can extract the workflow to identify the cause of failure.

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