While conducting literature research for my bachelor thesis about Anomaly Interpretation, I came across your paper "Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding" and found your research very insightful. The ASD dataset you published is particularly useful for my work.
However, I've encountered a challenge: the metric names in the dataset are represented by numbers (1, 2, ..., 19), which makes it difficult to identify the corresponding server metrics (CPU usage, RAM usage, etc.). I understand that this is done to protect the confidentiality of the data provider.
Is there any way to get a mapping of these numbers to their corresponding server metrics, or any additional context you can provide? Any information would be very helpful and will be used for research purposes only.
Thank you for your time and help. I look forward to your reply.
Hello,
I hope this message finds you well.
While conducting literature research for my bachelor thesis about Anomaly Interpretation, I came across your paper "Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding" and found your research very insightful. The ASD dataset you published is particularly useful for my work.
However, I've encountered a challenge: the metric names in the dataset are represented by numbers (1, 2, ..., 19), which makes it difficult to identify the corresponding server metrics (CPU usage, RAM usage, etc.). I understand that this is done to protect the confidentiality of the data provider.
Is there any way to get a mapping of these numbers to their corresponding server metrics, or any additional context you can provide? Any information would be very helpful and will be used for research purposes only.
Thank you for your time and help. I look forward to your reply.
Best regards