@inproceedings{92381faf51994b3fa226198671cf8b06,
title = "A personalized recommendation algorithm based on Hadoop",
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.",
keywords = "Big Data, Parallelization, Personalized Recommendation, Sparse Matrix Partition",
author = "Hao Huang and Jianqing Huang and Ziavras, {Sotirios G.} and Yaojie Lu",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 5th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2015 ; Conference date: 14-05-2015 Through 16-05-2015",
year = "2015",
month = sep,
day = "29",
doi = "10.1109/ICEIEC.2015.7284569",
language = "English (US)",
series = "ICEIEC 2015 - Proceedings of 2015 IEEE 5th International Conference on Electronics Information and Emergency Communication",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "406--409",
editor = "Vincent Tam and Zhu Wei and Li Wenzheng",
booktitle = "ICEIEC 2015 - Proceedings of 2015 IEEE 5th International Conference on Electronics Information and Emergency Communication",
address = "United States",
}