[Updated on Apr. 18] Integration of CiNii Articles into CiNii Research


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  • Network Failure Detection System based on Tweet Analysis Using Machine Learning and Statistical Anomaly Detection

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Mobile communication networks are indispensable as a life infrastructure, and a stable supply of network services is required. On the other hand, in the SNS such as Twitter, the real-world situation sensed by the user is shared in real time. Therefore, it is possible to grasp the events that occur in the real world by analyzing posts to SNS. In this paper, we propose a system for detecting network failures by classifying posts related to network failures by machine learning and detecting anomalies in the time series of the number of posts. Furthermore, the proposed system was evaluated by actual network failure cases.



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