Bacterial colony algorithms applied to association rule mining in static data and streams

Abstract

Bacterial colonies perform a cooperative and distributed exploration of the environmental resources. This paper describes how bacterial colony networks and their skills to search resources can be used as tools for mining association rules in static and stream data. The proposed algorithm is designed to maintain diverse solutions to the problems at hand, and its performance is compared to another well-known bacterial algorithm in both static and stream datasets.