> boulder selections Would that mean more rock and less bluegrass? (I'm kidding, of course) In all seriousness though, the problem probably is the data set to

> boulder selections Would that mean more rock and less bluegrass? (I'm kidding, of course) In all seriousness though, the problem probably is the data set to a certain extent. I am pretty adventurous, true, but at the same time I think the problem is that regardless of what data we collect, we only have the ability to determine if something is inoffensive. All you need to do is look at a site that aggregates reviews like Yelp or Amazon, and read some reviews. 95% of reviews are either 1 star or 5 stars, and it's obvious from reading the text that the rating is meaningless. "I ordered the wrong item by mistake, 1 star" "Food is overpriced, but the bathrooms are clean and wait staff is attractive, 5 stars." I find star ratings most useful because people who rate things 2-4 stars generally have the most nuanced and productive things to say about the product, and actually rate things what they think they should be rated, rather than using the rating system as a vote for "rate this higher/lower." I don't think it's possible to actually come up with good recommendations based on user-reported like/dislike rating. It's not wrong for a user to dislike a song because it reminds them of an ex, but using that as a basis for a recommendation to someone else is entirely useless. Systems like Rotten Tomatoes works really well in this regard, but almost has the opposite problem, which is that it tends to underrate movies with broad appeal, but that's generally not a problem since users will be exposed to those movies anyways.