Abstract
Telecommunication networks continuously generate various system logs which include plentiful information of system status. So these logs can be used to detect whether a network is under a fault scenario or not. In this paper, we propose an improved word mover's distance (WMD) called Topic Word Mover's Distance (T-WMD) to measure the distance between two log samples and then classify different fault logs to determine the fault root cause. Compared with original WMD, T-WMD takes topic information into consideration and provides more latent semantic information of log corpus. Experiments of k-nearest neighbor (k-nn) fault logs classification show that our T-WMD metric outperforms the original WMD.
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