Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Efficient repeating pattern finding in music databases
Proceedings of the seventh international conference on Information and knowledge management
Melodic matching techniques for large music databases
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Affect computing in film through sound energy dynamics
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
A music recommendation system based on music data grouping and user interests
Proceedings of the tenth international conference on Information and knowledge management
A Personalized Music Filtering System Based on Melody Style Classification
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Affective content detection using HMMs
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Extracting information about emotions in films
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Automatic multimedia cross-modal correlation discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Affect-based indexing and retrieval of films
Proceedings of the 13th annual ACM international conference on Multimedia
Toward automatic extraction of expressive elements from motion pictures: tempo
IEEE Transactions on Multimedia
Affective video content representation and modeling
IEEE Transactions on Multimedia
The role of user mood in movie recommendations
Expert Systems with Applications: An International Journal
Using affective parameters in a content-based recommender system for images
User Modeling and User-Adapted Interaction
Proceedings of the 9th ACM SIGGRAPH Conference on Virtual-Reality Continuum and its Applications in Industry
Impact of implicit and explicit affective labeling on a recommender system's performance
UMAP'11 Proceedings of the 19th international conference on Advances in User Modeling
Music recommendation using text analysis on song requests to radio stations
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
With the growth of digital music, the development of music recommendation is helpful for users to pick desirable music pieces from a huge repository of music. The existing music recommendation approaches are based on a user's preference on music. However, sometimes, it might better meet users' requirement to recommend music pieces according to emotions. In this paper, we propose a novel framework for emotion-based music recommendation. The core of the recommendation framework is the construction of the music emotion model by affinity discovery from film music, which plays an important role in conveying emotions in film. We investigate the music feature extraction and propose the Music Affinity Graph and Music Affinity Graph-Plus algorithms for the construction of music emotion model. Experimental result shows the proposed emotion-based music recommendation achieves 85% accuracy in average.