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
exibility and adaptability, and its ability to produce
intelligible rules of considerable complexity.
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