Product recommendation system using optimal switching hybrid algorithm. (5th March 2021)

• Record Type: Journal Article
• Authors: Bhuvaneshwari, P.; Rao, A. Nagaraja
• Is Part Of: International journal of intelligent enterprise. Volume 8:Number 2/3(2021)
• Page Start: 185
• Page End: 204
• Publication Date: 2021-03-05
• Subjects: e-commerce -- collaborative filtering -- cold start problem -- optimal switching hybrid approach -- OSHA -- K-nearest neighbour; Organizational learning -- Periodicals; Knowledge management -- Periodicals; Business intelligence -- Periodicals; Business enterprises -- Design -- Periodicals; Organizational effectiveness -- Periodicals; 658.005
• Languages: English
• ISSNs: 1745-3232

Abstract

The recommendation system works as a heart in the business strategy of e-commerce. By employing various techniques and methods it recommends the desirable items to the user. Recent studies suggest by applying proper methods the accuracy of the recommendation can be improved. Traditional techniques like collaborative filtering face the cold start problem, so in this paper, we propose an optimal switching hybrid approach (OSHA) to overcome the issue. Here, K-nearest neighbour algorithm is used to predict the similar kind of users and the experimental results show that the proposed algorithm performs better than the standalone technique.