![](/static/253f0d9b/assets/icons/icon-96x96.png)
![](https://lemmy.ml/pictrs/image/d3d059e3-fa3d-45af-ac93-ac894beba378.png)
While probably computationally too expensive, I would like some system where up/downvoting isn’t about objective quality, but only about personal preference. Essentially the system would “cluster” up/downvote behavior from users like youtube clusters like/dislike of videos and then recommend posts which people who like the same content as you like and people who dislike content you like dislike. I am not sure how many clusters/dimensions you would need though and I guess individualized sorting would quickly become computationally prohibitive as you would have to do a scalar multiplication of the post-dimensions with the user-dimensions for each post and then sort the stuff.
It’s hours/money spent/$ per hour split on paid/free games / non-games according to the link.
Pretty useful, but obviously does not know about bundles etc.