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How to efficiently separate "Trending Posts" from "Hot Posts" in real time using Redis?

Right now I'm using Reddit's ranking algorithm implemented in PHP with Redis but I can't find an efficient way to separate Trending Posts from Hot Posts in real time. I don't really have one definition for "Trending" /"Hot" right now because I haven't found a way to implement it in real time. In a few words, "Trending" would be new posts that have gained some importance but still aren't "important" enough to be on the hot list. And "Hot" posts would be those posts that have exceeded some predefined "importance threshold". I'm using "importance" here an abstract indicator because I'm willing to use any kind of metric that allows me to separate "Trending" from "Hot" posts in real time but I can't find a way to do it efficiently.
Answer:

I would: Collect per-post popularity features at real time. Impressions/clicks/shares in the past 1 / 5 / 10 / 30 / 60 etc. minutes. Also bucketed by user categories. Manually label some posts as "hot" and some posts as "trending". Instead of coming up with any definition, just look at the data. Yourself, or involve someone you could provide another less biased opinion. Train a model. Evaluate & A/B test it.

Dima Korolev at Quora Visit the source

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