Sherri Harms
ABSTRACT
This paper describes the application of data mining techniques in a Geo-spatial Decision Support System, which focuses on drought risk management. Association rule discovery is one of the widely used approaches in data mining. This paper highlights the rule discovery algorithms that we have developed and used for discovering useful patterns in ocean parameters and climatic indices to monitor drought.
- S. Harms, J. Deogun, J. Saquer, and T. Tadesse. Discovering representative episodal association rules from event sequences using frequent closed episode sets and event constraints. In Proceedings of the 2001 IEEE International Conference on Data Mining, pages 603--606, San Jose, California, USA, November 29 - December 2 2001a. Google Scholar
Digital Library
- S. Harms, S. Goddard, S. E. Reichenbach, W. J. Waltman, and T. Tadesse. Data mining in a geospatial decision support system for drought risk management. In Proceedings of the 2001 National Conference on Digital Government Research, pages 9--16, Los Angelos, California, USA, May 2001b. Google ScholarDigital Library
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- A. Silberschatz and A. Tuzhilin. On subjective measures of interestingness in knowledge discovery. In Proceedings of the First International Conference on Knowledge Discovery and Data Mining {KDD 95}, pages 275--281, Montreal, Canada, August 1995.Google Scholar
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Index Terms
- Efficient rule discovery in a geo-spatial decision support system
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