Demystifying algorithm Co recommendation: statistics, classification and distribution are woven into an information cage

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shormilaKhatun
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Demystifying algorithm Co recommendation: statistics, classification and distribution are woven into an information cage

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When it comes to algorithm recommendation, the first word Costa Rica Phone Number that may flash in most people's minds is "Today's Toutiao". Indeed, ByteDance's Toutiao, Douyin Costa Rica Phone Number and other products have left a deep impression on the public with the help of recommendation algorithms.In fact, in addition to ByteDance, Alibaba has widely used recommendation algorithms in Tmall, Taobao, NetEase in NetEase Cloud Music, and Station B in the video recommendation Costa Rica Phone Number stream. It is no exaggeration to say that in the Internet industry, as long as it is not direct information that users are actively looking for, there are even recommendation algorithms behind advertisements.

In 1994, the GroupLens research group of the Costa Rica Phone Number University of Minnesota in the United States launched the first automated recommendation system Costa Rica Phone Number GroupLens, which proposed the use of collaborative filtering as an important technology for recommending systems, and was also one of the earliest automated collaborative filtering recommendation Costa Rica Phone Number layman's terms, algorithm recommendation is an app that uses big data science to "fortune-telling" for users.

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Four years later (1998), Amazon launched Costa Rica Phone Number an item-based collaborative filtering algorithm, which is the earliest commercial case of algorithmic recommendation. Later, Facebook, Netflix, and even Chinese Costa Rica Phone Number companies such as ByteDance and Alibaba have widely used algorithmic recommendation. . In fact, the algorithm Costa Rica Phone Number recommendation is not complicated. To sum it up, it is the six words of "statistics, classification, and distribution" of information.
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