Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Similarity-based queries for time series data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Finding patterns in time series: a dynamic programming approach
Advances in knowledge discovery and data mining
Event correlation using rule and object based techniques
Proceedings of the fourth international symposium on Integrated network management IV
Proceedings of the fourth international symposium on Integrated network management IV
Production workflow: concepts and techniques
Production workflow: concepts and techniques
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
On Similarity Queries for Time-Series Data: Constraint Specification and Implementation
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
A Case-Based Reasoning Approach to the Resolution of Faults in Communication Networks
Proceedings of the IFIP TC6/WG6.6 Third International Symposium on Integrated Network Management with participation of the IEEE Communications Society CNOM and with support from the Institute for Educational Services
Proceedings of the IFIP TC6/WG6.6 Third International Symposium on Integrated Network Management with participation of the IEEE Communications Society CNOM and with support from the Institute for Educational Services
Landmarks: A New Model for Similarity-Based Pattern Querying in Time Series Databases
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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A novel method for analyzing time-series data and extracting time-correlations (time-dependent relationships) among multiple time-series data streams is described. The application of time-correlation detection in business impact analysis (BIA) is explained on an example. The method described in this paper is the first one that can efficiently detect and report time-dependent relationships among multiple time-series data streams. Detected time-correlation rules explain how the changes in the values of one set of time-series data streams influence the values in another set of time-series data streams. Those rules can be stored digitally and fed into various data analysis tools, such as simulation, forecasting, impact analysis, etc., for further analysis of the data. Performance experiments showed that the described method is 95% accurate, and has a linear running time with respect to the amount of input data.