Label
Frequency: 12 Issue per year
Paper Submission: Throughout the Month
Acceptance Notification: Within 2 days
Areas Covered: Multidisciplinary
Accepted Language: Multiple Languages
Journal Type: Online (e-Journal)
ISSN Number:
2582-8568
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 and 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.
e-commerce, Electronic Commerce, online shopping, Recommender System, Item-Based filtering Collaborative filtering, Demographic Analysis.