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Highly Recommended: Collaborative Filtering Gives Customers What They Want

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Netflix Top Picks, Amazon recommendations, the iTunes Genius button. They all have one thing in common: they are driven by clever algorithms that use a technique known as collaborative filtering. Often used in machine learning operations, collaborative filtering is the process by which a firm like Netflix generates predictions about a single user's preferences using data taken from a large number of users. This technical note offers an overview of three of the main collaborative filtering methods: slope one, a purely predictive nonparametric model; ordinal logit, a parametric regression model; and alternative least squares, a matrix factorization technique.

【書誌情報】

ページ数:11ページ

サイズ:A4

商品番号:HBSP-UV7839

発行日:2019/8/23

登録日:2019/10/30

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