/FML

Implementation of the IEEE TII paper titled "Unraveling Metric Vector Spaces withFactorization for Recommendation"

Primary LanguagePython

Use Python 3.5 or higher version.

The revision of this paper titled "Unraveling Metric Vector Spaces withFactorization for Recommendation" has been accepted by IEEE Transactions on Industrial Informatics.

If you use this code, please cite the following paper. Thank you very much.

@ARTICLE{8867947,
author={S. {Zhang} and L. {Yao} and B. {Wu} and X. {Xu} and X. {Zhang} and L. {Zhu}},
journal={IEEE Transactions on Industrial Informatics},
title={Unraveling Metric Vector Spaces with Factorization for Recommendation},
year={2019},
volume={},
number={},
pages={1-1},
keywords={Matrix converters;Task analysis;Extraterrestrial measurements;Sparse matrices;Informatics;Euclidean distance;Recommender Systems;Matrix Factorization;Collaborative Filtering},
doi={10.1109/TII.2019.2947112},
ISSN={},
month={},}