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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Simulated Annealing with Levy Distribution for Fast Matrix Factorization-Based Collaborative Filtering

Author 1: Mostafa A. Shehata Author 2: Mohammad Nassef Author 3: Amr A. Badr
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 9, No. 4 · Published 2018

DOI: https://doi.org/10.14569/IJACSA.2018.090445

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Abstract

Matrix factorization is one of the best approaches for collaborative filtering because of its high accuracy in presenting users and items latent factors. The main disadvantages of matrix factorization are its complexity, and are very hard to be parallelized, especially with very large matrices. In this paper, we introduce a new method for collaborative filtering based on Matrix Factorization by combining simulated annealing with levy distribution. By using this method, good solutions are achieved in acceptable time with low computations, compared to other methods like stochastic gradient descent, alternating least squares, and weighted non-negative matrix factorization.

Keywords

Simulated annealing levy distribution matrix factorization collaborative filtering recommender systems metaheuristic optimization

How to Cite this Article

Shehata, M. A., Nassef, M., & Badr, A. A. (2018). Simulated Annealing with Levy Distribution for Fast Matrix Factorization-Based Collaborative Filtering. International Journal of Advanced Computer Science and Applications, 9(4). https://doi.org/10.14569/IJACSA.2018.090445

Shehata, Mostafa A., et al.. "Simulated Annealing with Levy Distribution for Fast Matrix Factorization-Based Collaborative Filtering." International Journal of Advanced Computer Science and Applications, vol. 9, no. 4, 2018, https://doi.org/10.14569/IJACSA.2018.090445.

@article{Shehata2018,
  title     = {Simulated Annealing with Levy Distribution for Fast Matrix Factorization-Based Collaborative Filtering},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {4},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Mostafa A. Shehata and Mohammad Nassef and Amr A. Badr},
  doi       = {10.14569/IJACSA.2018.090445},
  url       = {https://doi.org/10.14569/IJACSA.2018.090445}
}

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