Parallelization of frequent Itemset mining methods with FP-tree : an experiment with PrePost+ algorithm

Joint Authors

Jamsheela, Olakara
Gopalakrishna, Raju

Source

The International Arab Journal of Information Technology

Issue

Vol. 18, Issue 2 (31 Mar. 2021), pp.208-213, 6 p.

Publisher

Zarqa University Deanship of Scientific Research

Publication Date

2021-03-31

Country of Publication

Jordan

No. of Pages

6

Main Subjects

Information Technology and Computer Science

Abstract EN

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.

American Psychological Association (APA)

Jamsheela, Olakara& Gopalakrishna, Raju. 2021. Parallelization of frequent Itemset mining methods with FP-tree : an experiment with PrePost+ algorithm. The International Arab Journal of Information Technology،Vol. 18, no. 2, pp.208-213.
https://search.emarefa.net/detail/BIM-1430917

Modern Language Association (MLA)

Jamsheela, Olakara& Gopalakrishna, Raju. Parallelization of frequent Itemset mining methods with FP-tree : an experiment with PrePost+ algorithm. The International Arab Journal of Information Technology Vol. 18, no. 2 (Mar. 2021), pp.208-213.
https://search.emarefa.net/detail/BIM-1430917

American Medical Association (AMA)

Jamsheela, Olakara& Gopalakrishna, Raju. Parallelization of frequent Itemset mining methods with FP-tree : an experiment with PrePost+ algorithm. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 2, pp.208-213.
https://search.emarefa.net/detail/BIM-1430917

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 212-213

Record ID

BIM-1430917