Frequent Item-set Mining For Electronics Data

Nikhil Ranjan Nayak

No d8u5b, OSF Preprints from Center for Open Science

Abstract: Data Analytics plays an important role in the decision-making process. Insights from such pattern analysis offer vast benefits, including increased revenue, cost cutting, and improved competitive advantage. However, the hidden patterns of the frequent item-sets become more time consuming to be mined when the amount of data increases over the time. Moreover, significant memory consumption is needed in mining the hidden patterns of the frequent item-sets due to a heavy computation by the algorithm. Therefore, an efficient algorithm is required to mine the hidden patterns of the frequent item-sets within a shorter run time and with less memory consumption while the volume of data increases over the time period.

Date: 2020-07-09
References: Add references at CitEc
Citations:

Downloads: (external link)
https://osf.io/download/5f2a8f595f705a02a861e752/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:d8u5b

DOI: 10.31219/osf.io/d8u5b

Access Statistics for this paper

More papers in OSF Preprints from Center for Open Science
Bibliographic data for series maintained by OSF ().