A personalized recommendation algorithm based on Hadoop

Document Type

Conference Proceeding

Publication Date

9-29-2015

Abstract

BDM-NBI algorithm is proposed at this paper. It focuses on the analysis of a personalized recommendation algorithm that utilizes a weighted bipartite graph suitable for processing big data. Our algorithm adopts bipartite graph partitioning using a vertex separator method that partitions a high-dimensional sparse matrix into a pseudo-block based diagonal matrix. Then, the recommendation algorithm analyzes all weighted sub-matrices in parallel. We produce the global recommendation weighted matrix by merging all of the sub-matrices in parallel. Experiments with Hadoop show that our algorithm has good approximation for small matrices and excellent scalability.

Identifier

84958641720 (Scopus)

ISBN

[9781479972838]

Publication Title

Iceiec 2015 Proceedings of 2015 IEEE 5th International Conference on Electronics Information and Emergency Communication

External Full Text Location

https://doi.org/10.1109/ICEIEC.2015.7284569

First Page

406

Last Page

409

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