@article{ART003084088},
author={Qi Zhang},
title={Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={5},
pages={177-187},
doi={10.9708/jksci.2024.29.05.177}
TY - JOUR
AU - Qi Zhang
TI - Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 5
PB - The Korean Society Of Computer And Information
SP - 177
EP - 187
SN - 1598-849X
AB - 177-Existing music recommendation systems do not sufficiently consider the discrepancy between the intended emotions conveyed by song lyrics and the actual emotions felt by users. In this study, we generate topic vectors for lyrics and user comments using the LDA model, and construct a user preference model by combining user behavior trajectories reflecting time decay effects and playback frequency, along with statistical characteristics. Empirical analysis shows that our proposed model recommends music with higher accuracy compared to existing models that rely solely on lyrics. This research presents a novel methodology for improving personalized music recommendation systems by integrating emotion recognition and user behavior analysis.
KW - Music emotion recognition;User behavior trajectories;Online Music Recommendation System
DO - 10.9708/jksci.2024.29.05.177
ER -
Qi Zhang. (2024). Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis. Journal of The Korea Society of Computer and Information, 29(5), 177-187.
Qi Zhang. 2024, "Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis", Journal of The Korea Society of Computer and Information, vol.29, no.5 pp.177-187. Available from: doi:10.9708/jksci.2024.29.05.177
Qi Zhang "Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis" Journal of The Korea Society of Computer and Information 29.5 pp.177-187 (2024) : 177.
Qi Zhang. Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis. 2024; 29(5), 177-187. Available from: doi:10.9708/jksci.2024.29.05.177
Qi Zhang. "Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis" Journal of The Korea Society of Computer and Information 29, no.5 (2024) : 177-187.doi: 10.9708/jksci.2024.29.05.177
Qi Zhang. Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis. Journal of The Korea Society of Computer and Information, 29(5), 177-187. doi: 10.9708/jksci.2024.29.05.177
Qi Zhang. Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis. Journal of The Korea Society of Computer and Information. 2024; 29(5) 177-187. doi: 10.9708/jksci.2024.29.05.177
Qi Zhang. Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis. 2024; 29(5), 177-187. Available from: doi:10.9708/jksci.2024.29.05.177
Qi Zhang. "Enhancing Music Recommendation Systems Through Emotion Recognition and User Behavior Analysis" Journal of The Korea Society of Computer and Information 29, no.5 (2024) : 177-187.doi: 10.9708/jksci.2024.29.05.177
