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推荐算法个人学习笔记以及代码实战

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Zu3zz/Person-Recommendation-Algorithms

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Chap0 CF (collaborative filtering)

itemCf与userCf

详见文件夹CF

  • itemcf与usercf的优缺点
    • 推荐实时性 item快 点击了就可以推荐
    • 新用户/新物品的推荐
    • 推荐理由的可解释性
    • 使用场景
      • 性能层面 item适用于物品<<人数
      • 个性化层面考量

Chap1 LFM (latent factor model)

  • 工业界效果比较好
  • 什么是LFM算法
    • 输入是每一个user向量和item向量的点赞矩阵
  • 应用场景
    • user的item推荐度列表
    • item的相似度推荐列表
    • item之间的相似度隐含挖掘

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