论文笔记：A Generic Top-N Recommendation Framework For Trading-off Accuracy, Novelty, and Coverage - 代码天地

论文笔记：A Generic Top-N Recommendation Framework For Trading-off Accuracy, Novelty, and Coverage

其他 2019-02-27 20:14:06 阅读次数: 0

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转载自blog.csdn.net/qq_35771020/article/details/87854554

论文笔记：A Generic Top-N Recommendation Framework For Trading-off Accuracy, Novelty, and Coverage

论文笔记：Local Latent Space Models for Top-N Recommendation

论文笔记：Top-N Recommendation with High-Dimensional Side Information via Locality Preserving Projection

论文笔记：A Novel Top-N Recommendation Approach Based on Conditional Variational Auto-Encoder

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论文笔记：Friend Recommendation Considering Preference Coverage in Location-Based Social Networks

论文笔记：Expanded autoencoder recommendation framework and its application in movie recommendation

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论文笔记：Collaborative Denoising Auto-Encoders for Top-N Recommender Systems

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论文笔记：Analysis of Recommendation Algorithms for ECommerce

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