A Content-based system for music recommendation and visualization of user preferences working on semantic notions
A Content-based system for music recommendation and visualization of user preferences working on semantic notions
Citació
- Bogdanov D, Haro M, Fuhrmann F, Xambó A, Gómez E, Herrera P. A Content-based system for music recommendation and visualization of user preferences working on semantic notions. In: 2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI); 2011 Jun 13-15; Madrid, Spain. New Jersey: IEEE; 2011. p. 249-52. DOI: 10.1109/CBMI.2011.5972554
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Descripció
Resum
The amount of digital music has grown unprecedentedly during the last years and requires the development of effective methods for search and retrieval. In particular, contentbased preference elicitation for music recommendation is a challenging problem that is effectively addressed in this paper. We present a system which automatically generates recommendations and visualizes a user’s musical preferences, given her/his accounts on popular online music services. Using these services, the system retrieves a set of tracks preferred by a user, and further computes a semantic description of musical preferences based on raw audio information. For the audio analysis we used the capabilities of the Canoris API. Thereafter, the system generates music recommendations, using a semantic music similarity measure, and a user’s preference visualization, mapping semantic descriptors to visual elements.Descripció
Comunicació presentada a: 9th International Workshop on Content-Based Multimedia Indexing (CBMI) celebrat del 13 al 15 d'octubre de 2011 a Madrid, Espanya.