Effects of personal characteristics in control-oriented user interfaces for music recommender systems
Abstract Music recommender systems typically offer a “one-size-fits-all” approach with the same user controls and visualizations for all users. However, the effectiveness of interactive interfaces for music recommender systems is likely to be affected by individual differences. In this paper, we fir...
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Gespeichert in:
| Autor*in: |
Jin, Yucheng [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Nature B.V. 2019 |
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| Übergeordnetes Werk: |
Enthalten in: User modeling and user adapted interaction - Springer Netherlands, 1991, 30(2019), 2 vom: 25. Okt., Seite 199-249 |
|---|---|
| Übergeordnetes Werk: |
volume:30 ; year:2019 ; number:2 ; day:25 ; month:10 ; pages:199-249 |
| Links: |
|---|
| DOI / URN: |
10.1007/s11257-019-09247-2 |
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OLC205459668X |
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| 520 | |a Abstract Music recommender systems typically offer a “one-size-fits-all” approach with the same user controls and visualizations for all users. However, the effectiveness of interactive interfaces for music recommender systems is likely to be affected by individual differences. In this paper, we first conduct a comprehensive literature review of interactive interfaces in recommender systems to motivate the need for personalized interaction with music recommender systems, and two personal characteristics, visual memory and musical sophistication. More specifically, we studied the influence of these characteristics on the design of (a) visualizations for enhancing recommendation diversity and (b) the optimal level of user controls while minimizing cognitive load. The results of three experiments show a benefit for personalizing both visualization and control elements to musical sophistication. We found that (1) musical sophistication influenced the acceptance of recommendations for user controls. (2) musical sophistication also influenced recommendation acceptance, and perceived diversity for visualizations and the UI combining user controls and visualizations. However, musical sophistication only strengthens the impact of UI on perceived diversity (moderation effect) when studying the combined effect of controls and visualizations. These results allow us to extend the model for personalization in music recommender systems by providing guidelines for interactive visualization design for music recommender systems, with regard to both visualizations and user control. | ||
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| 650 | 4 | |a Personal characteristics | |
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| 700 | 1 | |a Htun, Nyi Nyi |4 aut | |
| 700 | 1 | |a Verbert, Katrien |4 aut | |
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10.1007/s11257-019-09247-2 doi (DE-627)OLC205459668X (DE-He213)s11257-019-09247-2-p DE-627 ger DE-627 rakwb eng 004 VZ Jin, Yucheng verfasserin (orcid)0000-0002-3926-7277 aut Effects of personal characteristics in control-oriented user interfaces for music recommender systems 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2019 Abstract Music recommender systems typically offer a “one-size-fits-all” approach with the same user controls and visualizations for all users. However, the effectiveness of interactive interfaces for music recommender systems is likely to be affected by individual differences. In this paper, we first conduct a comprehensive literature review of interactive interfaces in recommender systems to motivate the need for personalized interaction with music recommender systems, and two personal characteristics, visual memory and musical sophistication. More specifically, we studied the influence of these characteristics on the design of (a) visualizations for enhancing recommendation diversity and (b) the optimal level of user controls while minimizing cognitive load. The results of three experiments show a benefit for personalizing both visualization and control elements to musical sophistication. We found that (1) musical sophistication influenced the acceptance of recommendations for user controls. (2) musical sophistication also influenced recommendation acceptance, and perceived diversity for visualizations and the UI combining user controls and visualizations. However, musical sophistication only strengthens the impact of UI on perceived diversity (moderation effect) when studying the combined effect of controls and visualizations. These results allow us to extend the model for personalization in music recommender systems by providing guidelines for interactive visualization design for music recommender systems, with regard to both visualizations and user control. User control Personal characteristics Recommender systems Perceived diversity Acceptance Cognitive load User experience Tintarev, Nava aut Htun, Nyi Nyi aut Verbert, Katrien aut Enthalten in User modeling and user adapted interaction Springer Netherlands, 1991 30(2019), 2 vom: 25. Okt., Seite 199-249 (DE-627)130998494 (DE-600)1083524-6 (DE-576)029154456 0924-1868 nnns volume:30 year:2019 number:2 day:25 month:10 pages:199-249 https://doi.org/10.1007/s11257-019-09247-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 AR 30 2019 2 25 10 199-249 |
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10.1007/s11257-019-09247-2 doi (DE-627)OLC205459668X (DE-He213)s11257-019-09247-2-p DE-627 ger DE-627 rakwb eng 004 VZ Jin, Yucheng verfasserin (orcid)0000-0002-3926-7277 aut Effects of personal characteristics in control-oriented user interfaces for music recommender systems 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2019 Abstract Music recommender systems typically offer a “one-size-fits-all” approach with the same user controls and visualizations for all users. However, the effectiveness of interactive interfaces for music recommender systems is likely to be affected by individual differences. In this paper, we first conduct a comprehensive literature review of interactive interfaces in recommender systems to motivate the need for personalized interaction with music recommender systems, and two personal characteristics, visual memory and musical sophistication. More specifically, we studied the influence of these characteristics on the design of (a) visualizations for enhancing recommendation diversity and (b) the optimal level of user controls while minimizing cognitive load. The results of three experiments show a benefit for personalizing both visualization and control elements to musical sophistication. We found that (1) musical sophistication influenced the acceptance of recommendations for user controls. (2) musical sophistication also influenced recommendation acceptance, and perceived diversity for visualizations and the UI combining user controls and visualizations. However, musical sophistication only strengthens the impact of UI on perceived diversity (moderation effect) when studying the combined effect of controls and visualizations. These results allow us to extend the model for personalization in music recommender systems by providing guidelines for interactive visualization design for music recommender systems, with regard to both visualizations and user control. User control Personal characteristics Recommender systems Perceived diversity Acceptance Cognitive load User experience Tintarev, Nava aut Htun, Nyi Nyi aut Verbert, Katrien aut Enthalten in User modeling and user adapted interaction Springer Netherlands, 1991 30(2019), 2 vom: 25. Okt., Seite 199-249 (DE-627)130998494 (DE-600)1083524-6 (DE-576)029154456 0924-1868 nnns volume:30 year:2019 number:2 day:25 month:10 pages:199-249 https://doi.org/10.1007/s11257-019-09247-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 AR 30 2019 2 25 10 199-249 |
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Effects of personal characteristics in control-oriented user interfaces for music recommender systems |
| abstract |
Abstract Music recommender systems typically offer a “one-size-fits-all” approach with the same user controls and visualizations for all users. However, the effectiveness of interactive interfaces for music recommender systems is likely to be affected by individual differences. In this paper, we first conduct a comprehensive literature review of interactive interfaces in recommender systems to motivate the need for personalized interaction with music recommender systems, and two personal characteristics, visual memory and musical sophistication. More specifically, we studied the influence of these characteristics on the design of (a) visualizations for enhancing recommendation diversity and (b) the optimal level of user controls while minimizing cognitive load. The results of three experiments show a benefit for personalizing both visualization and control elements to musical sophistication. We found that (1) musical sophistication influenced the acceptance of recommendations for user controls. (2) musical sophistication also influenced recommendation acceptance, and perceived diversity for visualizations and the UI combining user controls and visualizations. However, musical sophistication only strengthens the impact of UI on perceived diversity (moderation effect) when studying the combined effect of controls and visualizations. These results allow us to extend the model for personalization in music recommender systems by providing guidelines for interactive visualization design for music recommender systems, with regard to both visualizations and user control. © Springer Nature B.V. 2019 |
| abstractGer |
Abstract Music recommender systems typically offer a “one-size-fits-all” approach with the same user controls and visualizations for all users. However, the effectiveness of interactive interfaces for music recommender systems is likely to be affected by individual differences. In this paper, we first conduct a comprehensive literature review of interactive interfaces in recommender systems to motivate the need for personalized interaction with music recommender systems, and two personal characteristics, visual memory and musical sophistication. More specifically, we studied the influence of these characteristics on the design of (a) visualizations for enhancing recommendation diversity and (b) the optimal level of user controls while minimizing cognitive load. The results of three experiments show a benefit for personalizing both visualization and control elements to musical sophistication. We found that (1) musical sophistication influenced the acceptance of recommendations for user controls. (2) musical sophistication also influenced recommendation acceptance, and perceived diversity for visualizations and the UI combining user controls and visualizations. However, musical sophistication only strengthens the impact of UI on perceived diversity (moderation effect) when studying the combined effect of controls and visualizations. These results allow us to extend the model for personalization in music recommender systems by providing guidelines for interactive visualization design for music recommender systems, with regard to both visualizations and user control. © Springer Nature B.V. 2019 |
| abstract_unstemmed |
Abstract Music recommender systems typically offer a “one-size-fits-all” approach with the same user controls and visualizations for all users. However, the effectiveness of interactive interfaces for music recommender systems is likely to be affected by individual differences. In this paper, we first conduct a comprehensive literature review of interactive interfaces in recommender systems to motivate the need for personalized interaction with music recommender systems, and two personal characteristics, visual memory and musical sophistication. More specifically, we studied the influence of these characteristics on the design of (a) visualizations for enhancing recommendation diversity and (b) the optimal level of user controls while minimizing cognitive load. The results of three experiments show a benefit for personalizing both visualization and control elements to musical sophistication. We found that (1) musical sophistication influenced the acceptance of recommendations for user controls. (2) musical sophistication also influenced recommendation acceptance, and perceived diversity for visualizations and the UI combining user controls and visualizations. However, musical sophistication only strengthens the impact of UI on perceived diversity (moderation effect) when studying the combined effect of controls and visualizations. These results allow us to extend the model for personalization in music recommender systems by providing guidelines for interactive visualization design for music recommender systems, with regard to both visualizations and user control. © Springer Nature B.V. 2019 |
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| container_issue |
2 |
| title_short |
Effects of personal characteristics in control-oriented user interfaces for music recommender systems |
| url |
https://doi.org/10.1007/s11257-019-09247-2 |
| remote_bool |
false |
| author2 |
Tintarev, Nava Htun, Nyi Nyi Verbert, Katrien |
| author2Str |
Tintarev, Nava Htun, Nyi Nyi Verbert, Katrien |
| ppnlink |
130998494 |
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| hochschulschrift_bool |
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| doi_str |
10.1007/s11257-019-09247-2 |
| up_date |
2024-07-03T23:38:54.172Z |
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1803603079777484800 |
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