Ranking Based Approach To Maximize Utility Of Recommender Systems
Ganesh Kumar S., Hari Krishna P · International Journal of Computer Trends and Technology · 2013
E-commerce applications that sell products online need to recommend suitable products to customers to fasten their decision making. The recommender systems are required in order to help users and also the businesses alike. There were many algorithms that came into existence to built recommender systems. However they focused on recommendation accuracy. They did not concentrate much on recommendation quality like diversity of recommendations. This paper introduces many item ranking algorithms that can produce diverse recommendations. While generating recommendations transactions of all users are considered. A prototype application is built to test the efficiency of the proposed recommender system. The empirical results revealed that the proposed ranking-based techniques for diverse recommendations are effective and can be used in real world applications.