Similar User Index-based MapReduce for Distributed Recommender Systems
Haesung Lee, Joonhee Kwon · Advanced science and technology letters · 2014
Due to the time complexity in composing recommendations, matrix factorization-based approaches are inefficient in dealing with large scale datasets. In this paper, we propose a similar user index- based parallel matrix factorization approach. Since the group of similar users is indexed in advance, there is no need to compute similarities between all users in datasets. Furthermore, the size of a matrix is reduced because the matrix is only composed of indexed user's ratings and items. The current advanced cloud computing including Hadoop, MapReduce and Amazon EC2 are employed to implement the proposed approaches.