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Table 4 Results of the evaluation of Algorithm 2 over the Steve.Museum dataset

From: Efficient semi-automated assessment of annotations trustworthiness

# Tags per % Training      Time
reputation set covered Accuracy Precision recall F-measure (sec.)
clustered results (cut = 0.3)
5 18% 0.71 0.80 0.84 0.82 707
10 27% 0.70 0.79 0.83 0.81 1004
15 33% 0.70 0.79 0.84 0.82 1197
20 39% 0.70 0.79 0.84 0.82 1286
25 43% 0.71 0.79 0.85 0.82 3080
30 47% 0.72 0.79 0.86 0.82 3660
  1. Results of the evaluation of Algorithm 2 over the Steve.Museum dataset for training sets formed by aggregating 5, 10, 15, 20, 25 and 30 reputations per user. We report the percentage of dataset actually covered by the training set, the accuracy, the precision, the recall and the F-measure of our prediction.