Music Recommendation System Design Based on Gaussian Mixture Model
Yang Lu, Xuemei Bai, Feng Wang
Available Online December 2015.
- https://doi.org/10.2991/icmmcce-15.2015.182How to use a DOI?
- Gaussian Mixture Model; Music Classification; Music Recommendation
- The paper establishes a double-layer classifier based on Gaussian Mixture Model and the Thayer model to divide the music style into several categories. On the basis of effective verification of experiments, the music listening experience is added into the model to analyze and normalize two-dimensional data points and the tastes of music users or playing times also can be added to obtain new three-dimensional data points. Then the Gaussian Mixture Model is employed again for classifying the new three-dimensional data points. In this way, not only can the taste changing process of users for different music be analyzed, but also the similarity among different users can be calculated. Therefore, music can be recommended properly to music users.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yang Lu AU - Xuemei Bai AU - Feng Wang PY - 2015/12 DA - 2015/12 TI - Music Recommendation System Design Based on Gaussian Mixture Model BT - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015 PB - Atlantis Press SP - 1242 EP - 1247 SN - 2352-538X UR - https://doi.org/10.2991/icmmcce-15.2015.182 DO - https://doi.org/10.2991/icmmcce-15.2015.182 ID - Lu2015/12 ER -