Precision@k is a metric used to evaluate the quality of recommendations in information retrieval and recommender systems. It measures the proportion of relevant items found in the top 'k' results returned by a model, providing insight into how well the model performs when suggesting items to users. This metric is crucial for assessing the effectiveness of matrix completion techniques, as it directly relates to user satisfaction and the overall success of recommendation systems.
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