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Table 4 Mean absolute error (MAE) measurements for the four subgroups and four personalized recommendation algorithms. NMF (in bold) outperforms all other algorithms for all subgroups. Among the subgroups, the best accuracy results (i.e., lowest MAE scores) are reached by \(U_{\text{ambi}}\), while the worst accuracy results (i.e., highest MAE scores) are reached by \(U_{\text{hard}}\). To facilitate comparison, we also show the MAE measurements for the BeyMS and MS user groups

From: Support the underground: characteristics of beyond-mainstream music listeners

Subgroup

UserItemAvg

UserKNN

UserKNNAvg

NMF

\(U_{\text{folk}}\)

63.2143

70.3049

67.4406

57.2278

\(U_{\text{hard}}\)

65.1464

73.1949

69.2855

59.6887

\(U_{\text{ambi}}\)

60.5558

69.8315

65.5708

54.2073

\(U_{\text{elec}}\)

62.2894

71.0387

66.1499

56.6209

BeyMS

63.4608

71.6694

67.5856

57.7703

MS

61.2562

68.4894

63.3985

54.8182