Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce

Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce

Information overload is one of the most serious problems in big data environment, recommendation systems is a way to effectively mitigate the problem. In order to make use of rich user feedback and social networks information and to further improve the performance of the recommendation system ,This...

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Main Authors: Dong Jie, Qin Yun, Sun Xue Yang, Du Li Ming
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:MATEC Web of Conferences
Online Access:http://dx.doi.org/10.1051/matecconf/20166304018
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spelling doaj-b56019b9f3cd4681855c7c33a707b1e72021-04-02T10:08:45ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01630401810.1051/matecconf/20166304018matecconf_mmme2016_04018Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduceDong Jie0Qin YunSun Xue Yang1Du Li Ming2Information and Control Engineering College, Shenyang Jianzhu universityInformation and Control Engineering College, Shenyang Jianzhu universityInformation and Control Engineering College, Shenyang Jianzhu universityInformation overload is one of the most serious problems in big data environment, recommendation systems is a way to effectively mitigate the problem. In order to make use of rich user feedback and social networks information and to further improve the performance of the recommendation system ,This thesis makes a improvement on the user-based collaborative filtering algorithm by normalization method, Meanwhile the algorithm could be run on the MapReduce in the Hadoop platform. The experimental results show that the algorithm on Hadoop platform can effectively improve the accuracy of the data to recommend and computational efficiency, so as to improve the satisfaction of users.http://dx.doi.org/10.1051/matecconf/20166304018
collection DOAJ
language English
format Article
sources DOAJ
author Dong Jie
Qin Yun
Sun Xue Yang
Du Li Ming
spellingShingle Dong Jie
Qin Yun
Sun Xue Yang
Du Li Ming
Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce
MATEC Web of Conferences
author_facet Dong Jie
Qin Yun
Sun Xue Yang
Du Li Ming
author_sort Dong Jie
title Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce
title_short Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce
title_full Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce
title_fullStr Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce
title_full_unstemmed Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce
title_sort research on improved collaborative filtering recommendation algorithm on mapreduce
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2016-01-01
description Information overload is one of the most serious problems in big data environment, recommendation systems is a way to effectively mitigate the problem. In order to make use of rich user feedback and social networks information and to further improve the performance of the recommendation system ,This thesis makes a improvement on the user-based collaborative filtering algorithm by normalization method, Meanwhile the algorithm could be run on the MapReduce in the Hadoop platform. The experimental results show that the algorithm on Hadoop platform can effectively improve the accuracy of the data to recommend and computational efficiency, so as to improve the satisfaction of users.
url http://dx.doi.org/10.1051/matecconf/20166304018
work_keys_str_mv AT dongjie researchonimprovedcollaborativefilteringrecommendationalgorithmonmapreduce
AT qinyun researchonimprovedcollaborativefilteringrecommendationalgorithmonmapreduce
AT sunxueyang researchonimprovedcollaborativefilteringrecommendationalgorithmonmapreduce
AT duliming researchonimprovedcollaborativefilteringrecommendationalgorithmonmapreduce
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