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Table 9 RMSE comparison between ActivePMFv2 and ActivePMFv1 (A smaller RMSE means a better performance)

From: An online-updating algorithm on probabilistic matrix factorization with active learning for task recommendation in crowdsourcing systems

No. of selected samples T[N]W[Reli]+T[MaxDiff]W[N] + T[MaxDiff]W[Reli] (ActivePMFv2) T[N]W[Reli] + T[MaxDiff]W[Reli] (ActivePMFv1)
1000 0.7101 0.7101
2000 0.6097 0.6097
3000 0.5110 0.5110
4000 0.2710 0.4164
5000 0.2594 0.3180
6000 0.2513 0.2621
7000 0.2479 0.2566
8000 0.2494 0.2563
9000 0.2030 0.2054
10000 0.1116 0.1259
11000 0.0845 0.0880