Performance of Clustering Technique During Data Mining to Analyze Big Data

Authors

  • Dr. Kapil Kumar Kaswan  Assistant Professor, Department of CSE, CDLU, Sirsa, Haryana, India
  • Preeti  M.Tech. Scholar, Department of CSE, CDLU, Sirsa, Haryana, India

Keywords:

Big Data, Data mining, clustering, Map Reduce, Performance

Abstract

Data mining is the act of searching through big data sets to find patterns and correlations that, when analyzed, might assist solve issues faced by businesses. The methodologies and tools of data mining provide businesses with the ability to forecast future trends and make better educated business choices. Finding unique groupings, or "clusters," within a data collection is the objective of the clustering technique. Using an algorithm written in machine language, the tool produces groups in which the individual objects in each group will, in most cases, share characteristics with the other members of the group. The major challenge to big data processing is management of unmanaged data. Map reduce function is used to get the frequency of unmanaged data and makes it manageable. Moreover soft computing mechanism might be used to improve the performance of clustering operations. Present research is focused on enhancement of performance of clustering techniques that are used in data mining.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-08-30

Issue

Volume 9, Issue 4, July-August-2023

Section

Research Articles

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How to Cite

[1]
Dr. Kapil Kumar Kaswan, Preeti, " Performance of Clustering Technique During Data Mining to Analyze Big Data" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 4, pp.124-130, July-August-2023.