Why not just have the customer opt-in/out of 'algorithm participation' per movie selection?
Likely, Netflix has the power to start it's own social network platform based on it's existing users' movie preferences. Some user's might be proud to say that they rate specific movies highly, and correlate to particular algorithms based on collective opinions.
For instance: 'Click here to add user X's preferences to your algorithm for Y genre'
It's been a while since the flurry of de-anonymizing data papers back in 07-08, but my takeaway impression was that you can't truly de-anonymize large datasets without destroying its utility.
I imagine gender and DoB factor in heavily to something like a recommendation engine, and I'm sure zip code would come into play when trying to get those last couple percent as is the case with the Netflix prizes.
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Netflix Prize 3: How to create a meaningful database that is impossible to de-anonymize.
Why not just have the customer opt-in/out of 'algorithm participation' per movie selection?
Likely, Netflix has the power to start it's own social network platform based on it's existing users' movie preferences. Some user's might be proud to say that they rate specific movies highly, and correlate to particular algorithms based on collective opinions.
For instance: 'Click here to add user X's preferences to your algorithm for Y genre'
Funny, yes, but I honestly think they should consider this.
It's been a while since the flurry of de-anonymizing data papers back in 07-08, but my takeaway impression was that you can't truly de-anonymize large datasets without destroying its utility.
There's lots of ongoing work on the topic, new conferences, etc. One of the keywords is "privacy preserving data mining".
Indeed.
See this: http://godplaysdice.blogspot.com/2009/12/uniquely-identifyin...
I imagine gender and DoB factor in heavily to something like a recommendation engine, and I'm sure zip code would come into play when trying to get those last couple percent as is the case with the Netflix prizes.
Thats too bad. Sounds like an interesting research area.