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2018 | OriginalPaper | Chapter

Bacterial Colony Algorithms Applied to Association Rule Mining in Static Data and Streams

Authors : Danilo S. da Cunha, Rafael S. Xavier, Daniel G. Ferrari, Leandro N. de Castro

Published in: Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection

Publisher: Springer International Publishing

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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.

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Title: Bacterial Colony Algorithms Applied to Association Rule Mining in Static Data and Streams
Authors: Danilo S. da Cunha
Rafael S. Xavier
Daniel G. Ferrari
Leandro N. de Castro
Publisher: Springer International Publishing
Book: Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection
Print ISBN: 978-3-319-94778-5

Electronic ISBN: 978-3-319-94779-2

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-94779-2_45

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