Distributed formal concept analysis algorithms based on an iterative MapReduce framework

Xu, Biao and De Fréin, Ruairí and Robson, Eric and Ó Foghlú, Mícheál (2012) Distributed formal concept analysis algorithms based on an iterative MapReduce framework. In: Formal Concept Analysis - 10th International Conference, ICFCA 2012, Proceedings :. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . UNSPECIFIED, BEL, pp. 292-308. ISBN 9783642298912

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Abstract

While many existing formal concept analysis algorithms are efficient, they are typically unsuitable for distributed implementation. Taking the MapReduce (MR) framework as our inspiration we introduce a distributed approach for performing formal concept mining. Our method has its novelty in that we use a light-weight MapReduce runtime called Twister which is better suited to iterative algorithms than recent distributed approaches. First, we describe the theoretical foundations underpinning our distributed formal concept analysis approach. Second, we provide a representative exemplar of how a classic centralized algorithm can be implemented in a distributed fashion using our methodology: we modify Ganter's classic algorithm by introducing a family of algorithms, namely MRGanter and MRGanter+ where the prefix denotes the algorithm's lineage. To evaluate the factors that impact distributed algorithm performance, we compare our algorithms with the state-of-the-art. Experiments conducted on real datasets demonstrate that MRGanter+ is efficient, scalable and an appealing algorithm for distributed problems.

Item Type:	Book Section
Uncontrolled Keywords:	/dk/atira/pure/subjectarea/asjc/2600/2614
Departments or Groups:
Depositing User:	Admin SSL
Date Deposited:	19 Oct 2022 23:16
Last Modified:	07 Jun 2023 18:39
URI:	http://repository-testing.wit.ie/id/eprint/5049

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