Hybrid recommendation and parallelization of movies based on spark

DOI

10.2991/macmc-17.2018.81How to use a DOI?

Keywords

collaborative filtering, recommendation algorithm, huge data, spark.

Abstract

With the exponential growth of Internet data,the traditional stand-alone computational model has been unable to solve the real-time precise recommendation items in a complex and huge data,and the defect of traditional recommendation algorithm has become more obvious,this paper studies the collaborative filtering algorithm and matrix decomposition method,designs a parallel computing architecture based on spark,and a movie recommendation based on hybrid recommendation algorithm [1],the experimental results show that in a certain extent improves the recommendation accuracy and scalability,and has good acceleration effect.

Copyright

© 2018, 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/).

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TY  - CONF
AU  - Mengpu Zhou
AU  - Yu Liu
PY  - 2018/01
DA  - 2018/01
TI  - Hybrid recommendation and parallelization of movies based on spark
BT  - Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017)
PB  - Atlantis Press
SP  - 437
EP  - 442
SN  - 2352-5401
UR  - https://doi.org/10.2991/macmc-17.2018.81
DO  - 10.2991/macmc-17.2018.81
ID  - Zhou2018/01
ER  -