Competitive recommendation algorithm for E-commerce
Umutoni Nadine, Huiying Cao, Jiangzhou Deng · 2016
Collaborative filtering (CF) is commonly used and successful techniques in recommendation systems (RS) but it has showed some problems like sparsity and cold start. Different techniques are employed to overcome the collaborative problems but there is no one single algorithm which can satisfy the personalized needs of each user. This paper presents a new hybrid recommendation approach to improve the effectiveness through the competition process among a series of algorithms. Experiment has been conducted on MovieLens to verify our proposed approach. The results indicate that our approach enabled more efficient and stable recommendation than single method.