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Most work in graph-based recommender systems considers a {\em static} setting where all information about test nodes (i.e., users and items) is available upfront at training time.
Using linear algebra for intelligent information retrieval
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Efficient Non-Sampling Factorization Machines for Optimal Context-Aware Recommendation. In Proceedings of The Web Conference 2020 . 2400–2410
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