PRODUCT RECOMMENDATION IN MARKET BASKET ANALYSIS

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DC Field	Value	Language
dc.contributor.author	Anitha G	-
dc.contributor.author	Kavin Mozhi T	-
dc.date.accessioned	2020-09-28T06:16:06Z	-
dc.date.available	2020-09-28T06:16:06Z	-
dc.date.issued	2020-03	-
dc.identifier.isbn	2347-6648	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/1783	-
dc.description.abstract	Market Basket Analysis plays an important role in analytics. It is used in the retail showrooms to determine the place and sales of products, promotion for different types of customers to improve customer satisfaction and increase the profit of the retailers.This study deals with the concept of market basket analysis with the Apriori algorithm. The concept of the Apriori algorithm is to identify all the frequent itemsets. Through these frequent sets, able to derive association rules, these rules must satisfy minimum support threshold and minimum confidence threshold. It allows retailers to determine the relationship between the items that are purchased by their customers.	en_US
dc.language.iso	en	en_US
dc.publisher	Parishodh Journal	en_US
dc.subject	Market Basket Analysis	en_US
dc.subject	Apriori Algorithm	en_US
dc.subject	Retailers	en_US
dc.subject	Lift	en_US
dc.subject	Confidence	en_US
dc.subject	Support	en_US
dc.subject	Minimum Threshold	en_US
dc.title	PRODUCT RECOMMENDATION IN MARKET BASKET ANALYSIS	en_US
dc.type	Article	en_US
Appears in Collections:	International Journals

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