Comment by majormajor
4 days ago
Neat! It's a validation of the model that 75%+ of the recommendations are things I've read and also enjoyed, with a few "read, didn't like" and some more "didn't read, don't really want to."
But I think to break the content-bubble effects to find the longer tail, some way to reject or blacklist things - and have that be taken into effect in the model - might help.
To add to this Youtube afaik uses multiple models to sprinkle in new content alongside your usual recommendation just for this.
Likewise, I put in six of my favorites and had already read (and enjoyed) 29 of the 30 recommendations (I'll have to check out Blindsight by Watts). Working great but it would be cool - as with pretty much every recommendation algorithm ever - to have more of a "discovery" capability.