Hi, I am wondering what the best way is to implement recommendations based on click through rates. What I have: - user id - resource (i.e. item) - click through count for user on that resource
I'm reading Mahout in Action MEAP right now (very good so far). Mahout seems to be very preference based (votings/ratings) but I know (reading Mahout in Action) that it also supports preference-less recommendations. However, since I have a click through count preference-less recommendation seems to be throwing away this click through data. I wondered if I can somehow convert click through count to a preference or if I should take another approach. Some ideas I had: - Just use the click through count as the preference (knowing that different users will have widely different counts). - Normalize the click count across users to say a 0-100 scale - ok, that's it...only two ideas so far! Any suggestions/patterns? Any warnings/anti-patterns? It seems like this should be a really common use-case for recommendations. Cheers, Simon -- Simon Reavely [email protected]
