[mywittyname]

It's much easier to build a rec-engine that uses user data to make recommendations than it is to design one that analyzes intrinsic properties of items to build recommendations. Think how Spotify recommends music based on what other people who listen to this song like. This favors popular music. They could build an engine that analyzes musical characteristics to make recommendations, which would eliminate the popularity bias, but introduce others.

[jointpdf]

Actually Spotify does more than collaborative filtering. Here’s a superb blog post on using convolutional filters on the spectrograms to build content-based recommendations: https://benanne.github.io/2014/08/05/spotify-cnns.html