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This article needed a lot more info about the psychologist's approach to make it interesting, it was 90% background and the barest hint at the end about what he

by dood 19y ago

This article needed a lot more info about the psychologist's approach to make it interesting, it was 90% background and the barest hint at the end about what he is actually doing. For all we know he may have just made minor tweaks to some existing algorithm.

mixmax 19y ago
He mentions that he is inspired by Daniel Kahnemann, who has done work in behavioral economics. He won a nobel prize in 2002 that can be seen here: http://nobelprize.org/nobel_prizes/economics/laureates/2002/kahneman-lecture.html http://nobelprize.org/nobel_prizes/economics/laureates/2002/... The lecture explains quite well what he does, and also gives a hint at what is being done in the netflix prize contest.
mdemare 19y ago
Exactly. I mean, who cares about what Netflix' headquarters look like? Or what university his daughter goes to? Sometimes it feel like these journalists are just filling in a template.
cainus 19y ago
The article mentions tweaking the algorithm to take the timing of ratings into account. It gives the example that a person might rate two movies as 3/5, and a third they watch right after as a 4/5, because it was better than the previous two, but under normal(ized) circumstances that user would've given the 3rd movie a 3/5 too. Soo.... it's an interesting notion, that there can be time-segment-based normalization of the data set. Team Bellkor/KorBell credit a big part of their gains to using the ordering of rankings, rather than the rankings themselves to test for similarity, so this guy's actually got a novel approach for normalizing the dataset. I really don't know how he can detect if he's dealing with the kind of person that is meticulous enough to make sure their new ratings take all their previous ratings into account, though, or if he's dealing with the kind of person that gives everything a rating from 4/5 to 5/5.. I wouldn't be surprised if he hits a wall because of this. Really I think netflix would make a lot better strides towards their goals by improving their data collection technique. They could probably make great enhancements towards normalization just by saying "you gave this previous movie 3/5 stars. How do you rate this latest movie?" That way the data would be much more normalized. There are lots of possibilities for this sort of enhancement, so I'm not sure why they're only letting competitors look at the already collected dataset.

by dood 19y ago

mixmax 19y ago

He mentions that he is inspired by Daniel Kahnemann, who has done work in behavioral economics. He won a nobel prize in 2002 that can be seen here: http://nobelprize.org/nobel_prizes/economics/laureates/2002/kahneman-lecture.html http://nobelprize.org/nobel_prizes/economics/laureates/2002/... The lecture explains quite well what he does, and also gives a hint at what is being done in the netflix prize contest.

mdemare 19y ago

Exactly. I mean, who cares about what Netflix' headquarters look like? Or what university his daughter goes to? Sometimes it feel like these journalists are just filling in a template.

cainus 19y ago

The article mentions tweaking the algorithm to take the timing of ratings into account. It gives the example that a person might rate two movies as 3/5, and a third they watch right after as a 4/5, because it was better than the previous two, but under normal(ized) circumstances that user would've given the 3rd movie a 3/5 too. Soo.... it's an interesting notion, that there can be time-segment-based normalization of the data set. Team Bellkor/KorBell credit a big part of their gains to using the ordering of rankings, rather than the rankings themselves to test for similarity, so this guy's actually got a novel approach for normalizing the dataset. I really don't know how he can detect if he's dealing with the kind of person that is meticulous enough to make sure their new ratings take all their previous ratings into account, though, or if he's dealing with the kind of person that gives everything a rating from 4/5 to 5/5.. I wouldn't be surprised if he hits a wall because of this. Really I think netflix would make a lot better strides towards their goals by improving their data collection technique. They could probably make great enhancements towards normalization just by saying "you gave this previous movie 3/5 stars. How do you rate this latest movie?" That way the data would be much more normalized. There are lots of possibilities for this sort of enhancement, so I'm not sure why they're only letting competitors look at the already collected dataset.