DocumentCode :
2239472
Title :
The research and design of parallel recommendation algorithm based on mapreduce
Author :
Juan Yang ; Han Du ; Bin Wu ; Xinxin Ge
Author_Institution :
Beijing Key Lab. of Intell. Telecommun. Software & Multimedia, Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2012
fDate :
Oct. 30 2012-Nov. 1 2012
Firstpage :
303
Lastpage :
307
Abstract :
The rapid development of Internet technology has brought the problem of information overload, and recommendation algorithm is put forward and considered to be the most effective way to solve the problem. Most of the traditional research about recommendation algorithm is focused on accuracy and diversity. However, in the practical engineering application, massive data process will be the most serious problem. In this paper, we propose a parallel recommendation algorithm based on mapreduce programming model, which runs on Hadoop platform, and in our system, we use mongodb as our auxiliary storage data. Finally, we give some experiments to prove our algorithm is suitable for processing massive data.
Keywords :
Internet; parallel algorithms; recommender systems; Hadoop platform; Internet technology; MapReduce programming model; Mongodb; auxiliary storage data; information overload problem; massive data processing; parallel recommendation algorithm; Accuracy; Algorithm design and analysis; Collaboration; Programming; Random access memory; Resource management; Software algorithms; Mapreduce; Massive data process; Parallel algorithm; Recommendation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
Type :
conf
DOI :
10.1109/CCIS.2012.6664417
Filename :
6664417
Link To Document :
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