Time Series Abstraction Methods - A Survey
Informatik bewegt: Informatik 2002 - 32. Jahrestagung der Gesellschaft für Informatik e.v. (GI)
Clustering of time-series subsequences is meaningless: implications for previous and future research
Knowledge and Information Systems
Hadoop: The Definitive Guide
Why does subsequence time-series clustering produce sine waves?
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
InfraWatch: data management of large systems for monitoring infrastructural performance
IDA'10 Proceedings of the 9th international conference on Advances in Intelligent Data Analysis
MDL-Based analysis of time series at multiple time-scales
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
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Since 2008, a sensor network deployed on a major Dutch highway bridge has been monitoring various structural and environmental parameters, including strain, vibration and climate, at different locations along the infrastructure. The aim of the InfraWatch project is to model the structural health of the bridge by analyzing the large quantities of data that the sensors produce. This paper focus on the identification of traffic events (passing cars/trucks, congestion, etc.). We approach the problem as a time series subsequence clustering problem. As it is known that such a clustering method can be problematic on certain types of time series, we verified known problems on the InfraWatch data. Indeed, some of the undesired phenomena occurred in our case, but to a lesser extent than previously suggested. We introduce a new distance measure that discourages this observed behavior and allows us to identify traffic events reliably, even on large quantities of data.