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Volume & Issue no: Volume 10, Issue 3, May - June 2021

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Title:
A hybrid parallel algorithm for knowledge discovery in massive online education data set
Author Name:
Dr.B.Lavanya, P.Devipriya
Abstract:
Abstract: Discovering hidden knowledge from massive data has applications in varied disciplines. This research work focuses on both pattern mining techniques and massive data pattern analysis with the use of vertical mapping parallel implementation hybrid algorithm. It offers huge benefits including increased sales, cost-saving, enhanced competitive advantage, and mine information with the minimum time of execution using less memory. The main goal of this work is to analyze the users behaviors for decision-making. Traditional methods are not designed to manage massive databases because the amount of data grows over time; it takes more time to discover a frequent pattern. Therefore, an effective algorithm is required; the proposed hybrid algorithm has overcome this problem. In this paper, massive data is used to test hybrid algorithms which show that the parallel implementation is scalable, more effective than others, reduces the execution time in addition to feature extraction. Keywords: Big Data Analysis, Predictive Analysis, Machine learning, Parallel algorithm.
Cite this article:
Dr.B.Lavanya, P.Devipriya , " A hybrid parallel algorithm for knowledge discovery in massive online education data set" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 10, Issue 3, May - June 2021 , pp. 011-016 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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