Songs That Stick

One of the arguments put forth in the Herlocker survey is that if you ask a person to rate a song several times over the course of a few months, they are highly unlikely to give the same answer every time.

They describe this as a “natural variability” in human preference that perhaps represents a hard limit to how effective recommender systems can be.

While I do agree that preference is the product of a chaotic system influenced by variables many of which are unavailable to the computer system, it is true that much of the variability is encompassed by simple and easy to capture information. For example, I sometimes listen to dub when I’m writing code, because I can ignore it, but it would be completely inappropriate for working out. If the computer knew the types of music I liked while coding it could do a better job of pulling stuff for that category.

François is working on stuff to address the problem by allowing an explicit weighting of tags. Paul mentioned automatic characterization of tags such that I might have a “coding music” tag that is recognized as being situational rather than genre or mood, and specifically that the computer will figure out the category of that tag rather than me specifying it.

Another tact that I think will ultimately be necessary is to model preference as a time series characteristic rather than something static. What I like today is simply not the same thing that I will like tomorrow. The plasticity of the mind is undeniable (though there is certainly a neophyte / neophobe continuum along which most people lie).

I would not at all be surprised if there are characteristics common to songs that I have continued to like over the course of years and other characteristics common to songs that I liked for bit but have fallen out of favor. The changes are not just noise, they are important predictive data.

Maybe I’ll tackle that. Right after, I manage to write a baby collaborative filter. Who am I to let a complete lack of knowledge prevent me from doing something. ☺

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