collaborative filtering - What are some ways for a recommendation engine to deal with one time, novel and potentially important content? -

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say built recommendation engine recommend live tv shows watch. regular shows, pretty job using collaborative filtering , like. 1969 moon landing. it's important event, want recommendation engine handle case. can't rely on past behavior since value of recommendation drops 0 once show over.

what effective methods deal problem in recommendation space?

the problem in cf opposite: new items no clicks / ratings yet can't recommended cf algorithm , have trouble getting in front of users. old, famous item ought recommendable.

there's opposite problem: recommender system algorithms tend favor famous items knows rather more long-tail, lesser-known items may better recommendations in sense.

sounds have notion item extra-good in sense. that's side information include crudely boosting estimated rating value amount. think effective approach that.


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