Framework of dynamic recommendation system for e-shopping

The popularity of online shopping is growing rapidly in modern virtual market. Generally, customers take decision to purchase goods based on their basic need and relative need. Shopkeepers play an important role to influence the customers in real market. Recommendation engine is nothing but a good automated shopkeeper. In this paper, we propose a model of dynamic recommendation system (DRS) for online market. Our proposed technique provides an intelligent solution model to overcome the problems of customers’ rating and their feedback by integrating market basket analysis, frequent item mining, bestselling items and customer personalization.

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