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• W3106450873 abstract "We propose a new hybrid algorithm that allows incorporating both user and item side information within the standard collaborative filtering technique. One of its key features is that it naturally extends a simple PureSVD approach and inherits its unique advantages, such as highly efficient Lanczos-based optimization procedure, simplified hyper-parameter tuning and a quick folding-in computation for generating recommendations instantly even in highly dynamic online environments. The algorithm utilizes a generalized formulation of the singular value decomposition, which adds flexibility to the solution and allows imposing the desired structure on its latent space. Conveniently, the resulting model also admits an efficient and straightforward solution for the cold start scenario. We evaluate our approach on a diverse set of datasets and show its superiority over similar classes of hybrid models." @default.
• W3106450873 created "2020-11-23" @default.
• W3106450873 creator A5004111307 @default.
• W3106450873 creator A5010009492 @default.
• W3106450873 date "2019-09-10" @default.
• W3106450873 modified "2023-10-18" @default.
• W3106450873 title "HybridSVD" @default.
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• W3106450873 doi "https://doi.org/10.1145/3298689.3347055" @default.
• W3106450873 hasPublicationYear "2019" @default.
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