RESEARCH OF THE EFFICIENCY OF THE APRIORI GROUP ALGORITHMS ON DIFFERENT DATABASE SIZES
DOI:
https://doi.org/10.30888/2663-5712.2020-06-01-012Keywords:
associative rules search algorithms, Apriori, AIS, linear implemen-tation, parallel implementation, Hadoop, MapReduce.Abstract
The results of the work analysis of associative rule search algorithms for handling Big data are presented in the paper. The most famous modifica-tions of Apriori algorithms for finding associative rules are considered. The re-sults of the research of thMetrics
References
Zayko T.A., Oleynik A.A., Subbotin S.A., “Associative rules in data mining”, Vestnik NTU "KHPI, no.39 (1012), pp. 82-96, 2013.
Belim S.V., Mayorov-Zilbernagel A.O., Seliverstov S.A., “Using associative rules to restore noisy images”, Vestnik Omskogo universiteta. Series "Information Technolo-gy", no. 4, pp. 197-200, 2013.
Billig V.A., Ivanova O.V., Tsaregorodtsev N.A., “The construction of associative rules in the task of medical diagnosis”, Programmnyye produkty i sistemy, no. 2 (114), 2016. https://cyberleninka.ru/article/n/postroenie-assotsiativnyh-pravil-v-zadache-meditsinskoy-diagnostiki.
Maslova N.O., Polovinka O.L., “Application of methods of search of associations at creation of tests on information security” [Zastosuvannya metodiv poshuku asotsiatsiy pry stvorenni testiv z informatsiynoyi bezpeky], Zbírnik naukovikh prats' Donets'kogo natsíonal'nogo tekhníchnogo uníversitetu. Seriya: “Computer science is a cybernetics and a calculating technique.”, no.1 (29), pp 47-53, 2019.
Subbotin S.A., Oleynik A.A., Hoffmann E.A., Zaitsev S.A., Oleinik Al.A. Intelligent information technology for designing automated systems for diagnosing and recogniz-ing images: monograph.. LLC "Company Smith" (2012), 317.
Adamo J.-M. Data mining for association rules and sequential patterns: sequential and parallel algorithms. Springer-Verlag (2001), 259.
S. Singh, R. Garg and P. K. Mishra, "Review of Apriori Based Algorithms on MapRe-duce Framework", 2014 International Conference on Communication and Computing (ICC - 2014), pp. 593–604, 2014.
Jyoti Yadav, Neha Sehta, “Implement Mapreduce Apriori Algorithm to Generate Fre-quent Itemsets”, International Journal of Computer Applications, Vol. 179., no.38, pp. 7-10, 2018.
Singh S, Garg R, Mishra PK., “Performance optimization of MapReduce-based Aprio-ri algorithm on Hadoop cluster”, Computers & Electrical Engineering, pp. 348-364, 2018. https://arxiv.org/ftp/arxiv/papers/1807/1807.06070.pdf.
Dmitrieva O.A., Polovinka O.L., “Algorithmic support for parallel methods of search-ing for associative rules”, Zbirnyk naukovykh pratsʹ Donetsʹkoho natsionalʹnoho tekhnichnoho universytetu. Series: "Computer Engineering and Automation", no.1 (31), pp. 62-69, 2018.
Agrawal R., Imielinski T., Swami A., “Mining association rules between sets of items in large databases”, In Proc. of the ACM SIGMOD Conference on Management of Data, 1993. https://rakesh.agrawal-family.com/papers/sigmod93assoc.pdf.
Online implementation of the Apriori algorithm. https://github.com/asaini/Apriori
Online implementation of AprioriTID algorithm. https://github.com/ymoch/apyori
Agrawal Rakesh, Ramakrishnan Srikant, “Fast algorithms for mining association rules”, Proc. 20th int. conf. very large data bases, VLDB, Vol. 1215, рр. 487-499, 1994.
Polovinka O., Nikulin D., Dmitrieva O., “Research of speed of work of a priori algorithms on data of large volumes” [Doslіdzhennya shvidkodії robots apіornyh algorithms on tribute to the great obligations]. Science and production. Series: Information Technology, no 22, pp. 246-253, 2020.
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