The New Algorithm of the Item-based on MapReduce

DOI

10.2991/ameii-16.2016.62How to use a DOI?

Keywords

Recommendation system parallel computing Clustering

Abstract

Traditional collaborative filtering algorithm based on item and K-means clustering algorithm are studied, the parallel algorithm of collaborative filtering Item-based on MapReduce is proposed by using MapReduce programming model. The algorithm is mainly divided into two steps, one step is K-Means algorithm clustering for users, another step is the parallel Item-based algorithm for clustering user recommendation. Experimental results show that the algorithm has obtained very good effect, improved the running speed and execution efficiency, the improved algorithm is much suitable for processing big data.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Wei Zhao
PY  - 2016/04
DA  - 2016/04
TI  - The New Algorithm of the Item-based on MapReduce
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SP  - 300
EP  - 304
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.62
DO  - 10.2991/ameii-16.2016.62
ID  - Zhao2016/04
ER  -