A survey of recommendation systems in big data

Information overload is one of most critical problems in big data, and recommendation systems which are powerful methods to solve this problem are coming under growing attention by industry and academia. The main task of recommendation systems in big data is to improve the performance and accuracy along with user satisfaction utilizing user feedback, social network and other information. A survey of the recommendation systems in the big data is proposed, which includes the summarization of big data and recommendation systems, the differences between the recommendation systems in traditional environment and in big data, key techniques, evaluation and typical applications according to a hierarchical framework. Finally, the prospects for future development and suggestions for possible extensions are also discussed. ©, 2015, Beijing University of Posts and Telecommunications. All right reserved.