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Titlebook: Knowledge Science, Engineering and Management; 13th International C Gang Li,Heng Tao Shen,Xiang Zhao Conference proceedings 2020 Springer N

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Deep Generative Recommendation with Maximizing Reciprocal Rankring at the top of the predicted recommendation list as possible. The experimental results demonstrated that the proposed method outperforms several state-of-the-art methods in ranking estimation task.
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Spatio-Temporal Attentive Network for Session-Based Recommendationdomness of user’s behaviors, is proposed to enrich item representations. Then we utilize attention mechanism to capture the user’s real purpose involved user’s initial will and main intention. Extensive experimental results on three real-world benchmark datasets show that STASR consistently outperfo
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Seeds Selection for Influence Maximization Based on Device-to-Device Social Knowledge by Reinforcemee computing tasks from the remote cloud to adjacent base stations (BSs). The experiment results on a realistic D2D data set show our method improves D2D coverage by 17.65% than heuristic average allocation. The cellular network traffic is reduced by 26.35% and the time delay is reduced by 63.53%.
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CIFEF: Combining Implicit and Explicit Features for Friendship Inference in Location-Based Social Newe propose a new explicit feature to capture the explicit information of user pairs who have common locations. Extensive experiments on two real-world LBSNs datasets show that our proposed method CIFEF can outperform six state-of-the-art methods.
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Sili Huang,Bo Yang,Hechang Chen,Haiyin Piao,Zhixiao Sun,Yi Chang
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