YouTube has risen to be one the biggest platform anyone can outsource information from. Well, apart from Google at the forefront, YouTube has turned to be home to many researchers. Commonly known for its Video search feature, which has attracted millions of users, YouTube is unarguably the best-recommended platform to fish your information.
Speaking of YouTube and videos, have you ever wondered how YouTube magically suggests similar videos to the one you searched for? You might be wondering how that is worked out. If you stick for a minute or two this article will outline how that is made possible.
To make this happen, there is a video recommendation suggestion system set up in place. This particular system facilitates what video will be recommended to you on YouTube’s homepage and in the “Up next” section. As promised earlier, let’s get into more details below.
How video recommendation suggestion system works
Just like any other site to fish out information, the main purpose of the recommendation suggestion system is to give out new information and suggest more content to the user regarding what he searches for. However, there are some factors the system considers to give correct recommendations;
Current watch and search history
The system analyses the user’s current and previous search history. Using this, the system easily collects the content of the same genre displaying it on the home screen and the up next section. This factor leads to YouTube growth as many satisfied users will be coming back to watch more suggested videos.
Channels subscribed to
Using the user’s current data on the channels subscribed to, the YouTube suggestion system uses this data to determine what channels the user loves to watch. Using this information, the system finds suitable videos to recommend to its users.
Mostly watched videos
Videos having the most viewers are also suggested on the home page. Such a video would mean that people enjoy it most thus the recommendation.
The suggestion system conducts surveys on the YouTube platform and other related apps. Direct feedback is used to determine which videos users would like for recommendations. Video recommendations help in subscriber growth as more users get to subscribe to recommended videos.
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