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Introduction to Recommender System. Part 1 (Collaborative Filtering, Singular Value Decomposition)by@huangkh19951228
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Introduction to Recommender System. Part 1 (Collaborative Filtering, Singular Value Decomposition)

by 黃功詳 Steeve Huang7mJanuary 24th, 2018
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A recommender system refers to a system that is capable of predicting the future preference of a set of items for a user, and recommend the top items. One key reason why we need a recommender system in modern society is that people have too much options to use from due to the prevalence of Internet. In the past, people used to shop in a physical store, in which the items available are limited. For instance, the number of movies that can be placed in a Blockbuster store depends on the size of that store. By contrast, nowadays, the Internet allows people to access abundant resources online. Netflix, for example, has an enormous collection of movies. Although the amount of available information increased, a new problem arose as people had a hard time selecting the items they actually want to see. This is where the recommender system comes in. This article will give you a brief introduction to two typical ways for building a recommender system, Collaborative Filtering and Singular Value Decomposition.

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黃功詳 Steeve Huang

黃功詳 Steeve Huang

@huangkh19951228

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