maxMF-Nonlinear Latent Factorization by Embedding Multiple User Interests
1：經典的推薦會採用矩陣分解方式來學習用戶、商品的潛在向量，並用用戶與商品向量的相似度來召回商品。 2：什麼是maxMF？ 這裏的maxMF區別去ALS是，它不像ALS只會有一個向量，他的前提假設是一個用戶更加複雜，我們不能靠一個單純的向量去表示用戶，我們需要多個向量去表示用戶，然後用一個向量去表示商品。這樣我們用戶與商品匹配得分就是取用戶多個向量裏那個最大得分作爲匹配得分。而且這個模型是一個非線
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