New hybrid recommendation system based On C-Means clustering method
Mohammad Hamidi Esfahani, Farid Khosh Alhan · 2013
Nowadays recommendation systems are widely used in E-Commerce. They can learn about user interests and automatically suggest the best product to the consumer. Most of these recommendation systems are using collaborative, content-based or knowledge-based method. Users and products can gather in some groups based on their similar features. Using these groups can improve their recommendations and help these systems to solve some problems (for example cold start problem). Many clustering methods used to in recommendation systems but a few of these methods are light or easy to use so they can make the recommendation process and user feedback faster, in the other hand, having a good recommendation is more useful than having too many recommendations that a few of them take the user attention. In this paper, a hybrid recommendation system with C-Means clustering method selected to have a better and faster recommendation system.