One of my applications includes user-generated posts and functions in a similar way to Instagram. When a user opens the app they see a feed of posts sorted by date. This works when there just one small demographic using the app, but as the user base becomes more diverse, not everyone is interested in the same posts. This is why apps like TikTok and Instagram have algorithms to decide which posts to show to a user. Where do I even start with this? I understand that there need to be tags on each post for what they are about (this is where I think I can use machine learning) and then each users information needs to include their interests (I’m not sure what can be used to change this as they like or dislike posts). Is there a simple pre-built way of doing this or any examples? It seems fo be a pretty big secret that mostly big tech companies understand and use.
Firebase - Machine Learning and interest tracking to create an algorithm for sorting posts
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You could use Google's "cloud vision api(For Images): https://cloud.google.com/vision" and "Video Intelligent Api(For videos): https://cloud.google.com/video-intelligence/docs". Video Intelligence Api could handle images too from byte stream. Build a firebase function that analyse posted media with these api. Build the rest of the logic from here. Find a way to detect their interest from post, save their interests.