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Market Basket Analysis using Association Rule Learning

IJCA Proceedings on Recent Trends in Future Prospective in Engineering and Management Technology
© 2016 by IJCA Journal
RTFEM 2016 - Number 2
Year of Publication: 2016
Nidhi Maheshwari
Nikhilendra K. Pandey
Pankaj Agarwal

Nidhi Maheshwari, Nikhilendra K Pandey and Pankaj Agarwal. Article: Market Basket Analysis using Association Rule Learning. IJCA Proceedings on Recent Trends in Future Prospective in Engineering and Management Technology RTFEM 2016(2):20-24, July 2016. Full text available. BibTeX

	author = {Nidhi Maheshwari and Nikhilendra K. Pandey and Pankaj Agarwal},
	title = {Article: Market Basket Analysis using Association Rule Learning},
	journal = {IJCA Proceedings on Recent Trends in Future Prospective in Engineering and Management Technology},
	year = {2016},
	volume = {RTFEM 2016},
	number = {2},
	pages = {20-24},
	month = {July},
	note = {Full text available}


The proposed paper focusses on the basic concepts of association rule mining and the market basket analysis of different items. In the current study, the market analysis would be done by collecting the real, primary data directly from retailers and wholesalers. The efficiency of the FP-Growth algorithm can be measured in terms of mining of the frequent pattern. Precisely, we apply FP-Growth algorithm on the various data collected from different stores in order to trace the various association rules comprising of a basket. One discrete advantage is that it avoids the generation of candidate sets, which is computationally exhaustive. The results and conclusions drawn can be used in optimizing the market. This will help in predicting future trends and behaviours, allowing businesses to make knowledge-driven decisions.


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