A Music Recommendation System Based on Annotations about Listeners' Preferences and Situations

Authors:
Katsuhiko Kaji;Keiji Hirata;Katashi Nagao
Affiliations:
Nagoya University;NTT Communication Science Laboratories;Nagoya University
Venue:
AXMEDIS '05 Proceedings of the First International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution
Year:
2005

Citing 0
Cited 3

An intelligent music playlist generator based on the time parameter with artificial neural networks

Expert Systems with Applications: An International Journal
Intelligent Music Playlist Recommendation Based on User Daily Behavior and Music Content

PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A context-aware multi-model remote controller for electronic home devices

The Journal of Supercomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a playlist generation scheme that uses lyrics and annotations to discover similarity between kinds of music and user tastes. It generates a playlist according to user preferences and situations. Additionally, users can provide some feedbacks to the system such as whether each tune is suitable for the preference and the situation. The system transforms the feature values concerning preferences and situations and adapts them to each user. The playlists are generated through three phases. First, an initial playlist is found from databases by content-based retrieval. Second, transcoding improves the playlist according to the user's preference and situation. Finally, by interaction between the system and the user, the playlist becomes more suitable for the user.