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