Concurrent frequent itemsets mining in a shared prefix tree using the Apriori algorithm

Marek Puścian

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.
Author Marek Puścian (FEIT / IN)
Marek Puścian ,,
- The Institute of Computer Science
Pages108082W-1-108082W-9
Publication size in sheets0.5
Book Romaniuk Ryszard, Linczuk Maciej Grzegorz (eds.): Proceedings of SPIE: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2018, Proceedings of SPIE: The International Society for Optical Engineering, vol. 10808, 2018, SPIE - the International Society for Optics and Photonics, ISBN 9781510622036, 2086 p., DOI:10.1117/12.2504983
Keywords in Englishalgorithm parallelization, shared memory, Apriori, frequent items mining, a measure of speed up.
DOIDOI:10.1117/12.2501692
URL https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10808/108082W/Concurrent-frequent-itemsets-mining-in-a-shared-prefix-tree-using/10.1117/12.2501692.full
projectDevelopment of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Arabas Jarosław, , Phone: +48 22 234 7432, start date 01-06-2017, end date 31-10-2018, II/2017/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
File
108082W_puscian.pdf 533.88 KB
Score (nominal)15
ScoreMinisterial score = 15.0, 11-12-2018, BookChapterSeriesAndMatConf
Ministerial score (2013-2016) = 15.0, 11-12-2018, BookChapterSeriesAndMatConf
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