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Currycomb/Item-Recommend-System
本项目的数据集给出了15万左右的用户以及12万左右的商品, 以及对应的经过脱敏处理的用户特征和经过预处理的商品特征,旨在为用户推荐50个其可能购买的商品。 推荐系统架构方案 本项目采用传统的召回+排序的方案。在召回模块采用deepwalk, node2vec,item ...
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