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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