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I have a project to model users with characteristic tags (e.g. runner, cyclist, swimmer, vegan, pianist) in order to correlate user behaviour to these labels. Obviously a user can have multiple characteristics (non-exclusive) and so the distance (or similarity) between users is determined by the amount of tag overlap.

  1. Is there a name for this kind of model?
  2. Are there any particular patterns/algorithms that are useful for measuring correlations in data represented by this kind of model?

I don't need a complete list; just to be pointed in the right direction.

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  • $\begingroup$ You can also try Fuzzy Set Theory, which allows for partial membership to non exclusive classes. $\endgroup$ – steadyfish Feb 26 '13 at 2:41
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In answer to your first question, I think you are looking for the jaccard distance.

I'm not aware of any particularly special methods for this metric, but it is a proper metric so most methods should be fine. Hopefully knowing the name will help!

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