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Concurrent frequent itemsets mining in a shared prefix tree using the Apriori algorithm
Author(s): Marek Puścian
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Paper Abstract

This paper presents a sequential frequent itemsets mining algorithm Apriori that is adapted to concurrent processing. It applies Master Slave scheme to candidate generation and support counting operations performed by threads on a single machine. Two approaches to traversing shared prefix tree and counting support of itemsets are presented and compared. Several optimization methods have been proposed for the multithreaded environment. Proposed enhancements have been successfully implemented using JAVA. This paper discusses results of the performance of concurrent Apriori algorithm against different datasets. Presented approach has been illustrated with many experiments and measurements performed using multiprocessor and multithreaded computer.

Paper Details

Date Published: 1 October 2018
PDF: 9 pages
Proc. SPIE 10808, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2018, 108082W (1 October 2018); doi: 10.1117/12.2501692
Show Author Affiliations
Marek Puścian, Warsaw Univ. of Technology (Poland)


Published in SPIE Proceedings Vol. 10808:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2018
Ryszard S. Romaniuk; Maciej Linczuk, Editor(s)

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