PRODUCT RECOMMENDATION IN MARKET BASKET ANALYSIS
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.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.identifier.isbn | 2347-6648 | |
dc.identifier.uri | https://dspace.psgrkcw.com/handle/123456789/1783 | |
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 |
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