DISGD: A Distributed Shared-nothing Matrix Factorization for Large Scale Online Recommender Systems
With the web-scale data volumes and high velocity of generation rates, it has become crucial that the training process for recom mender systems be a continuous process which is performed on live data, i.e., on data streams. In practice, such systems have to address three main requirements including...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2020
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| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/2927 https://openproceedings.org/2020/conf/edbt/paper_200.pdf https://doi.org/10.5441/002/edbt.2020.32 |
| الوسوم: |
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