Abstract
Discovering association rules is a well-established problem in the field of data mining, with many existing solutions. In later years, several methods have been proposed for mining rules from sequential and temporal data. This paper presents a novel technique based on genetic programming and specialized pattern matching hardware. The advantages of this method are its flexibility and adaptability, and its ability to produce intelligible rules of considerable complexity.
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Hetland, M.L., Sætrom, P. (2004). Temporal Rule Discovery using Genetic Programming and Specialized Hardware. In: Lotfi, A., Garibaldi, J.M. (eds) Applications and Science in Soft Computing. Advances in Soft Computing, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45240-9_13
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DOI: https://doi.org/10.1007/978-3-540-45240-9_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40856-7
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