focused data-mining

[cellio]

There is a service that I wish someone -- Amazon is an obvious candidate -- would provide to me, and I wonder how realistic it is. (It seems like it should be easy given the data, and they've surely got the data.)

Here's an example: I've bought three CDs from a particular artist. I really like two of them, and I don't care for the third. She has more CDs. Which (if any) am I likely to like? If I could find ratings for those CDs from people who liked the two I liked and didn't like the one I didn't like, that would be informative. Overall ratings of those products are irrelevant, because I don't know anything the raters. Reviews can be more informative but, again, I don't know how the reviewers' tastes match my own and most reviews are not well-written. User-submitted "if you like this buy that" links can be helpful but are under-used; they're also not annotated. Knowing that people also bought them isn't helpful; I bought the one I didn't like, too. I want to tap into the actual ratings (not purchase history) from a subset of raters -- the ones who match my own profile. Ratings are more reliable than the other options available because Amazon uses them to push things at you, so you're motivated to get them right.

I'm casting this in terms of Amazon because they're doing part of the problem already, but in theory this could be done by anyone who can mine the data.

Is anyone providing a service like this (with a large-enough user base to be relevant)? Does any Amazonian reading this want to run with it? :-)

Comments

I can't find it

[(Anonymous)]

On my blog (quite possibly before Christmas, back before the latest reboot (sigh), there was talk of a computer system that analyzed music based on computer analysis. For once, no humans were involved. The idea is that, being able to analyze large numbers of songs, the computer might find good stuff that's being overlooked.

As I remember, though, it wasn't ready for prime time. I also remember something about it using neural nets to do the analysis. That's actually problematic. Neural nets can find connections between things that humans don't care about. For example, a data set comparing images with and without tanks worked fine in training, but presented with new images not in either data set, the system couldn't determine if there was a tank in the picture. It seems that all the non-tank images were taken on sunny days and all the tank images on cloudy days. The computer completely missed the tanks and paid attention to sunny vs. non-sunny. Oops.

Rob of UnSpace (http://www.unspace.net/)

PS: Jupiter has a new red spot! (http://www.scienceblog.com/cms/jupiters_got_a_new_red_spot_10142.html) Wheee! Ok, so I get excited over really stupid stuff....

Re: I can't find it

[cellio]

I remember that post. I, too, had the impression that this was early research, but hey, maybe in several years ordinary folks like us will be able to make use of it.

Re: I can't find it

[(Anonymous)]

Well, I suspect that this might have been a comment from me (Gclectic), posting about Music Magic Mixer, which is still one of my favorite programs for generating playlists from the songs I already own. They also do provide services for recommending new albums based upon similarity to the acoustic characteristics of any album you specify, matching against the databases of either Amazon or , though this feature is indeed a little bit less reliable than their mainline playlist-generation feature.

For my full, in-depth, gushing review, you can check out this post (http://gclectic.typepad.com/gclectic/2005/08/my_favorite_sof.html) on my blog.

Re: I can't find it

[cellio]

Thanks for the pointer! This might get me to actually sit down and import a bunch of my music. (I'm still mostly in the world of physical media, I'm afraid.)