Parallelization of Frequent Itemset Mining Methods with FP-tree: An Experiment with PrePost+ Algorithm | Zendy

O. Jamsheela | Zendy; Raju Gopalakrishna | Zendy

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Parallelization of Frequent Itemset Mining Methods with FP-tree: An Experiment with PrePost+ Algorithm

Author(s) -

O. Jamsheela,

Raju Gopalakrishna

Publication year - 2021

Publication title -

the international arab journal of information technology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.227

H-Index - 27

eISSN - 2309-4524

pISSN - 1683-3198

DOI - 10.34028/iajit/18/2/9

Subject(s) - computer science , algorithm , graphics , field (mathematics) , tree (set theory) , data mining , mathematics , mathematical analysis , computer graphics (images) , pure mathematics

Parallel processing has turn to be a common programming practice because of its efficiency and thus becomes an interesting field for researchers. With the introduction of multi- core processors as well as general purpose graphics processing units, parallel programming has become affordable. This leads to the parallelization of many of the complex data processing algorithms including algorithms in data mining. In this paper, a study on parallel PrePost+ is presented. PrePost+ is an efficient frequent itemset mining algorithm. The algorithm has been modified as a parallel algorithm and the obtained result is compared with the result of sequential PrePost+ algorithm

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