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Table 2 Mean absolute error (MAE) results for the two user groups MS and BeyMS of different mainstreaminess and a selection of standard recommendation algorithms. A one-tailed Mann–Whitney-U test (\(\alpha = 0.0001\)) provides significant evidence, indicated by , that all algorithms perform worse on BeyMS than on MS in terms of MAE. Furthermore, NMF (as shown in bold) outperforms the other three approaches UserItemAvg, UserKNN and UserKNNAvg

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

User group UserItemAvg UserKNN UserKNNAvg NMF
BeyMS 63.4608 71.6694 67.5770 57.7703
MS 61.2562 68.4894 63.3985 54.8182
Overall 62.2315 69.8962 65.2469 56.2492