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1دورية أكاديمية
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s002Test
https://figshare.com/articles/journal_contribution/Summary_of_experimental_designs_built_for_regression_models_with_type_and_number_of_independent_features_for_each_model_/24661163Test -
2دورية أكاديمية
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s001Test
https://figshare.com/articles/journal_contribution/Demographic_breakdown_of_our_data_according_to_gender_and_age_/24661160Test -
3دورية أكاديمية
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s004Test
https://figshare.com/articles/journal_contribution/Model_significance_ANOVA_between_all_and_best_feature_models_/24661172Test -
4دورية أكاديمية
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience العلاقة: https://figshare.com/articles/journal_contribution/Complete_classification_results_/24661166Test
الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s003Test
https://figshare.com/articles/journal_contribution/Complete_classification_results_/24661166Test -
5دورية أكاديمية
المؤلفون: Ngoc-Huynh Ho, Hyung-Jeong Yang, Soo-Hyung Kim, Gueesang Lee
المصدر: IEEE Access, Vol 8, Pp 61672-61686 (2020)
مصطلحات موضوعية: Speech emotion recognition, multi-level multi-head fusion attention, RNN, audio features, textual features, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
وصف الملف: electronic resource
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6صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s005Test
https://figshare.com/articles/figure/Significant_correlations_i_ps_i_5_3_x_10_sup_5_sup_for_the_Individualising_and_Binding_moral_super-foundations_/24661175Test -
7صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s006Test
https://figshare.com/articles/figure/Feature_importance_for_the_Individualising_and_Binding_moral_super-foundations_/24661181Test -
8صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s009Test
https://figshare.com/articles/figure/Complete_Spearman_correlations_between_MFT_traits_and_pitch_features_/24661193Test -
9صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.g001Test
https://figshare.com/articles/figure/Overview_of_methodological_framework_/24661196Test -
10صورة
المؤلفون: Vjosa Preniqi, Kyriaki Kalimeri, Charalampos Saitis
مصطلحات موضوعية: Neuroscience, Sociology, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, top 5 songs, song 8217, meet individual needs, machine learning approach, facebook page likes, used basic features, acoustic features separately,
+music%22">xlink "> music, linking music preferences, participants 8217, likes per user, level audio features, audio features boosted, predicting moral values, capturing moral values, lyrics features obtained, preferred music artists, higher prediction scores, audio p, audio features, moral values, textual features, music rehabilitation, music experience الإتاحة: https://doi.org/10.1371/journal.pone.0294402.s007Test
https://figshare.com/articles/figure/Complete_Spearman_correlations_between_MFT_traits_and_lyrics_features_top_and_middle_panels_and_high-level_music_attributes_bottom_panel_/24661184Test