The Research and Application of MapReduce Based Neighbor Model in Personalized Recommendation

Jian Xi Peng; Zhi Yuan Liu

doi:10.4028/www.scientific.net/AMM.373-375.1674

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 373-375The Research and Application of MapReduce Based...

The Research and Application of MapReduce Based Neighbor Model in Personalized Recommendation

Abstract:

Personalized recommendation provides convenience to users and brings more benefit to companies as well. It has been an important part of electronic commerce website. Collaborative filtering is a common algorithm in recommendation system. But with massive data ages coming, traditional collaborative filtering algorithm could not finish recommendation in time. A neighbor model algorithm based on MapReduce distributed computing framework is presented against to collaborative filtering algorithm. The presented algorithm could accomplish the personalized recommendation effectively and meet the real time requirement completely. The simulation shows that the algorithm has high efficiency and could complete the recommended in a highly efficient and real-time.

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Periodical:

Applied Mechanics and Materials (Volumes 373-375)

Pages:

1674-1677

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.373-375.1674

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Online since:

August 2013

Authors:

Jian Xi Peng, Zhi Yuan Liu

Keywords:

Collaborative Filtering (CF), MapReduce, Neighbor Model, Recommendation System

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