Titlebook: Database Systems for Advanced Applications; 26th International C Christian S. Jensen,Ee-Peng Lim,Chih-Ya Shen Conference proceedings 2021 T

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https://doi.org/10.1057/978-1-137-53913-7aptive weight to emphasize the importance of few-shot users. We simulate the few-shot recommendation problem on three real-world datasets and extensive results show that SANS can outperform the state-of-the-art recommendation algorithms in few-shot recommendation.

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Introduction: American Fiction Abroad,s. Moreover, to better capture user preference and model news lifecycle, we present a User Preference LSTM and a News Lifecycle LSTM to extract sequential correlations from news representations and additional features. Extensive experimental results on two real-world news datasets demonstrate the si

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Introduction: American Fiction Abroad,references that can be hit more quickly and accurately. Finally, SeqCR utilizes the policy network to decide whether to recommend or ask. We conduct extensive experiments on two datasets from MovieLens 10M and Yelp in multi-round conversational recommendation scenarios. Empirical results demonstrate

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https://doi.org/10.1007/978-3-030-94166-6based neighbors in hyperedge efficiently. Moreover, it can conduct the embedding propagation of high-order correlations explicitly and efficiently in knowledge-aware hypergraph. Finally, we apply the proposed model on three real-world datasets, and the empirical results demonstrate that KHNN can ach

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Contemporary American Memoirs in Actionork to capture user interest drift across sessions. The other is a Multi-user Identification (MI) module, which draws on the attention mechanism to distinguish behaviors of different users under the same account. To verify the effectiveness of MISS, we construct two data sets with shared account cha