4 ms·
I agree that data is the main issue here. Most companies using recommendation algorithms are over-relying on math to do the magic and make up for the fact that
by Jinnidotcom 15y ago
I agree that data is the main issue here. Most companies using recommendation algorithms are over-relying on math to do the magic and make up for the fact that they are blind to what they are recommending. In order to recommend you photography related items based on your past interest in painting, the service would have to understand an awful lot about the two realms and what they have in common (art, visual, etc). Algorithms alone can't figure this out. No, I'm not blaming math, math can do amazing things to help us deal with situations where we have no data. But meaningful, accurate recommendations require meaningful, accurate information about the items being recommended. IA techniques can help automate the cataloguing of this information, but 'blind' algorithms alone will never make high quality recommendations - the kind that make you say 'Yes! Exactly!'
I aslo agree that social recommendations have to be able to pinpoint which friends have simialr taste, otherwise the result is just noise and junk.
Nikki
www.jinni.com
- deleted 15y ago[deleted]
- crasshopper 15y agoNikki, I would argue that it's not a case of "maths in general can't do this" but just that you may be using the wrong maths. You can't "just apply SVD" and expect that to work super well.