MATEC Web Conf.
Volume 63, 20162016 International Conference on Mechatronics, Manufacturing and Materials Engineering (MMME 2016)
|Number of page(s)||5|
|Section||Information Technology, Control and Application|
|Published online||12 July 2016|
Research on Improved Collaborative Filtering Recommendation Algorithm on MapReduce
1 Information and Control Engineering College, Shenyang Jianzhu university, Shenyang, 110168, China
2 Liaohe Oilfield Company SAGD Project Department
a Corresponding author: firstname.lastname@example.org
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.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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