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EEMR: An Emotion-Enhancing Hybrid Recommendation Mechanism for Music Playlists
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- Xu Feike
- Graduate School of ISEE, Kyushu University
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- Ma Boxuan
- Faculty of Arts and Science, Kyushu University
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- Konomi Shin’ichi
- Faculty of Arts and Science, Kyushu University
Description
<p>Affective states play a crucial role in music, as music can influence both current emotions and long-term moods. We propose a novel emotion-enhancing hybrid music recommendation (EEMR) mechanism that finds the suitable criteria in selecting the best music playlist for improving user’s emotion by combining two recommendation techniques, i.e., content-based filtering and context-aware approach. This mechanism generates playlists that align with the user’s preferences and current emotion, while also supporting gradual improvement of the user’s emotion over time.</p>
Journal
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- Special Interest Group on Web Intelligence and Interaction
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Special Interest Group on Web Intelligence and Interaction 20 (0), 79-86, 2024
Special Interest Group on Web Intelligence and Interaction
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Details 詳細情報について
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- CRID
- 1390303090621069696
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- ISSN
- 27582922
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Allowed