Comparing taste in films using pairwise vector comparisons

I'd be interested in reading a more general blog article about their theory behind using "quality" and "rewatchability" as their key user rating. It sounds reasonable at first, but when I think more deeply about it, I wonder what "quality" is supposed to be interpreted as. Is it "how much I enjoyed the <i>first</i> viewing of the film," something more specific like "how skillful was the camera work" or "how good was the acting," or something more meta like "how good I think <i>critics</i> or movie buffs would think the film is?"<p>I've gone through stages of armchair film criticism, so I've thought about personal ratings a lot. I even drafted a web app to track my viewings and watchlist, and the rating idea I've liked the most is a stupidly simple boolean rating. You could call it almost anything: "Like/Dislike," "Good/Bad," "Enjoyed/Didn't Enjoy," or even something a bit different like "I'm glad I watched it/I wish I hadn't watched it."

How is this better than a normalized cosine similarity? The vector being arbitrary, but in this case being a normalized value on quality and rewatchability.<p>Cosine similarity would also let you express pairwise similarity as a single normalized value, instead of a 9-way comparison.

Interesting read. Vector Victor sounds like a linear correlation algorithm. I wonder what coefficient they're using under the hood...

It's cool they're taking a new approach. I wonder if there aren't scientific papers on this stuff.