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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