Design of Robust Hybrid Recommender System For Optimal Business Decision Model In E-Commerce Digital Systems

CH. Surya Kiran, Abbineni Maheedhar, Moturika Ranjith, Ponneboina Harsha Vardhan, Miriyala Ramakrishna

Abstract


Now a day’s many e-commerce applications amount of data like products and its details, images, description, reviews etc. Recommender systems make life easier by making recommendations. In e-commerce, often some products doesn’t get sold or less profits are earned from the product. Identification of the reason behind the less profits from the product, was a difficult task. So we are proposing a hybrid recommender system that helps the item manufacturer to improve his product. We built a hybrid recommender system by combining various regression algorithms  along with backward elimination, CAR(Context-Aware Recommendation)model, user to user collaborative filtering. Finally the optimal business decision is taken by the manufacturer.

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