Bacterial colonies perform a cooperative distributed exploration of the environment. This paper describes bacterial colony networks and their skills to explore resources as a tool for mining association rules in databases. The proposed algorithm is designed to maintain diverse solutions to the problem at hand, and its performance is compared to other well-known bio-inspired algorithms, including a genetic and an immune algorithm (CLONALG) and, also, to Apriori over some benchmarks from the literature.
CITATION STYLE
da Cunha, D. S., Xavier, R. S., & de Castro, L. N. (2015). A bacterial colony algorithm for association rule mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9375 LNCS, pp. 96–103). Springer Verlag. https://doi.org/10.1007/978-3-319-24834-9_12
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