Recommendation Systems
MK and
Recommendation Systems
Feed Your Head, Choose Your Algorithm
youchoose.ai
as a network scales, it is inevitable that you need a way to sort & rank content.
web 2.0 solved it by ranking for popularity but a better approach could be to have a minimal quality threshold but not to try to rank things above that - so the search is not maximization-driven and leaves more room for serendipity.
h/t ken stanley
Towards Recommender System Optimization: Our Data Tool for Algorithmic Optimization on Spotify [Part 1]
Dmitry Pastukhovmusic-tomorrow.com![Thumbnail of Towards Recommender System Optimization: Our Data Tool for Algorithmic Optimization on Spotify [Part 1]](https://uploads-ssl.webflow.com/6206e1343aa2f122195717f8/6310b1a1447a22ac785a50ae_alina-grubnyak-ZiQkhI7417A-unsplash%20(1).jpg)
Today most algorithms that recommend or suppress content act purely on the basis of inferred popularity. They look at how much time people spend engaging with a piece of content, and boost it to more people if the numbers look good. The content itself is almost purely a black box. Some algorithms try to classify content with tags like “food” or
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