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In recommender systems, one-class collaborative filtering refers to the recommendation setting in which only positive interactions are observed, so missing entries mix true negatives with unseen positives. This meaning comes from Pan (2008) in 2008 Eighth IEEE International Conference on Data Mining.[1]
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