A study of Data Mining Techniques and Challenges

Authors

  • Suresh Kaswan Assistant Professor Department of Computer Science & Engineering, RIMT University, Mandi Gobindgarh, Punjab, India Author

DOI:

https://doi.org/10.55524/

Keywords:

Algorithms, Classification, Clustering, Data Mining, Database

Abstract

In digital era, such as now, expansion of  data in databases is quite quick; everything linked to  technology, such as social media, financial technology, & scientific data, all contribute significantly to data growth.  Because of enormous growth of information in this age of  networking & info distribution, manually evaluating,  categorising, & summarising data is difficult. As a result,  subjects like big data & data mining are frequently  explored. Data mining is procedure for dig out info from  huge amounts of data in order to create a pattern or  anomaly. In order to create innovative approaches for  incorporating uncertainty management into data mining,  this research looks into basics of data mining as well as  existing research on integrating uncertainty into data  mining. Management of indeterminate data, which might  be instigated by obsolete resources, specimen mistakes, or  inaccurate calculations, is among most difficult issues for technologies of data mining. Development of noval approaches for adding uncertainty supervision into data  mining will be a focus of future study. 

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Published

2022-03-30

How to Cite

A study of Data Mining Techniques and Challenges . (2022). International Journal of Innovative Research in Computer Science & Technology, 10(2), 92–95. https://doi.org/10.55524/