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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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.