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@article{148477,
        author = {Shikha Nandi},
        title = {Frequent Pattern Discovery Using Apriori Algorithm For Data Mining},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {6},
        number = {2},
        pages = {158-162},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=148477},
        abstract = {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 improve 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 behavior, 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 behavior of customers to know the items that are bought together frequently.},
        keywords = {Data Mining, Association Rule Mining, No SQL Database, Apriori Algorithm, Frequent Item Set, Customer Segmentation},
        month = {},
        }