J4 ›› 2015, Vol. 37 ›› Issue (08): 1444-1449.
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GAO Xianwei,SHI Zhibin
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Abstract:
Recommendation for new users in big data era is difficult and the efficiency is very low due to the lack of historical data. In order to solve these problems, we propose a new user recommendation algorithm, which combines the collaborative filtering algorithm based on the Mahout and the Top N algorithm based on the MapReduce. We build a new user recommendation system architecture, design and implement the Hadoop Top N algorithm and the collaborative filtering algorithm in the Mahout. Theoretical analysis and experimental results show that the proposed recommendation algorithm for big data processing has better recommended efficiency, scalability and quality than the collaborative filtering algorithm.
Key words: new user recommendation;Mahout;recommendation system;Hadoop;big data
GAO Xianwei,SHI Zhibin. Design and implementation of a new user recommendation algorithm based on Mahout [J]. J4, 2015, 37(08): 1444-1449.
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http://joces.nudt.edu.cn/EN/Y2015/V37/I08/1444