A Novel Neural Collaborative Filtering Recommendation Based on Side Information Fusion
Keywords:neural network, side information, denoising autoencoder, rating information
It is difficult to accurately learn user's latent features using only one single data source. In order to solve these problems, we consider to utilize relevant side information of users or items as a supplement to rating information to enhance the performance of recommender systems, and propose a novel neural collaborative filtering recommendation model based on side information fusion. Extensive experiments on different datasets validate the efficiency and accuracy of our proposed framework.
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LicenseCopyright (c) 2023 Proceedings of the Bulgarian Academy of Sciences
Copyright (c) 2022 Proceedings of the Bulgarian Academy of Sciences
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