Workflow extraction for service operation using multiple unstructured trouble tickets
Akio Watanabe, Keisuke Ishibashi, Tsuyoshi Toyono, Tatsuaki Kimura, Keishiro Watanabe, Yoichi Matsuo, Kohei Shiomoto · 2016
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.