Paper
1 October 2018 Concurrent frequent itemsets mining in a shared prefix tree using the Apriori algorithm
Author Affiliations +
Proceedings Volume 10808, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2018; 108082W (2018) https://doi.org/10.1117/12.2501692
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2018, 2018, Wilga, Poland
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.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marek Puścian "Concurrent frequent itemsets mining in a shared prefix tree using the Apriori algorithm", Proc. SPIE 10808, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2018, 108082W (1 October 2018); https://doi.org/10.1117/12.2501692
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KEYWORDS
Mining

Databases

Java

Detection and tracking algorithms

Algorithm development

Data modeling

Optimization (mathematics)

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