FMGAN: A Filter-Enhanced MLP Debias Recommendation Model Based on Generative Adversarial Network
In recommendation models, bias can distort the distribution of user-generated data, leading to inaccurate representation of user preferences. Failure to filter out biased data can result in significant learning errors, ultimately reducing the accuracy of the recommendation model. To address this iss...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-07-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/13/7975 |