Data Mining for Frequent Pattern Discovery using Apriori Algorithm |
Author(s): |
| Shailesh Shevalkar , jaywantrao sawant colleage of engineering hadapsar; Akash Gandhale, jaywantrao sawant colleage of engineering hadapsar |
Keywords: |
| Data Mining, Association Rule Mining, No SQL Database, Apriori Algorithm, Frequent Item Set, Customer Segmentation |
Abstract |
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We live in a fast changing digital world. In today’s age we expect the sellers to tell us what we might want to purchase. Most of us rely on popular website’s like Amazon’s recommendation system to but stuff. This gives the seller an interesting opportunity to increase their sales. If a seller can tell us what we might be interested in to buy, it doesn’t only improves their sales, but also the customer experience and life time value. On the other hand, seller is unable to predict the next purchase or our shopping behaviour, the customer or we might not go back to their store or website. In this paper, we will be implementing one such popular algorithm called Apriori algorithm with NoSQL Database that enables us to predict the shopping behaviour of customers to know the items that are bought together frequently. |
Other Details |
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Paper ID: IJSRDV7I40345 Published in: Volume : 7, Issue : 4 Publication Date: 01/07/2019 Page(s): 249-252 |
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