Optimization of Association Rules with Genetic Algorithms

As the databases grow in size, the interpretation of data within them, is increasingly difficult to obtain, and often only stored as backup of various transactions of records. In this data there is new information which is present, but requires a higher level of processing. This will create the association rules which are used to detect events that occur together in a set of data. To find these rules, a very popular algorithm in Data Mining is Apriori, which aims to reduce the search space and increase efficiency. In this research, we´ll introduce new metrics like interestingness and completeness with derived applications from Artificial Intelligence, "Genetic Algorithms", in order to reduce the search space and execution time.