Design and implementation of recommender system based on Hadoop
Qing Wang · 2016
Recommender system is to establish the relationship between the user and the information products, to use the existing selection habits and the similarity of each user's potential interest in the object, and then personalized recommendation. It is one of the effective ways to solve the information overload in the Internet age. But in practical application, because of the large number of products and the number of users, the traditional recommendation system is usually run on the single machine, which has been far from meeting the needs of such big data. In this paper, we design and implement a network recommendation algorithm based on Hadoop platform, which is based on the theory of Hadoop and Map/Reduce programming.