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Offline Approaches to Recommendation With Online Success
The problem of mismatching results between fully offline evaluations and fully online evaluations is really something that's very, very interesting to me. There are many papers over the years that have reported on this problem, but there really aren't many that have been able to solve it. But the sort of core of the problem is that we are measuring two different things. We show recommendations to users and we hope that they like them, which is a very vague statement that that's not very easy to measure. So if our fully online system should also focus on buying or clicking certain items, when there was no real data involved, that shouldn't be surprising. That's what we're going to measure in this