Pattern Discovery in Time-Ordered Data
- Sandia National Laboratories
This report describes the results of a Laboratory-Directed Research and Development project on techniques for pattern discovery in discrete event time series data. In this project, we explored two different aspects of the pattern matching/discovery problem. The first aspect studied was the use of Dynamic Time Warping for pattern matching in continuous data. In essence, DTW is a technique for aligning time series along the time axis to optimize the similarity measure. The second aspect studied was techniques for discovering patterns in discrete event data. We developed a pattern discovery tool based on adaptations of the A-priori and GSP (Generalized Sequential Pattern mining) algorithms. We then used the tool on three different application areas--unattended monitoring system data from a storage magazine, computer network intrusion detection, and analysis of robot training data.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (US); Sandia National Labs., Livermore, CA (US)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 793315
- Report Number(s):
- SAND2002-0245
- Country of Publication:
- United States
- Language:
- English
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