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For an up-to-date list of publications from the Music Technology Group see the
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Music Recommendation: A multi-faceted approach
| Title | Music Recommendation: A multi-faceted approach |
| Publication Type | Master Thesis |
| Year of Publication | 2006 |
| Authors | Celma, Ò. |
| preprint/postprint document | files/publications/7126eb-DEA-2006-Celma.pdf |
| Abstract |
This research project is about music recommendation. More precisely, it is concerned with the problems that appear when computer programs try to automatically recommend music assets to users. The aim of this work is to present a multi-faceted approach to the music recommendation problem.
Music recommendation involves the modelling of user preferences, as well as the matching between profiles and music related information. In recent years the typical music consumption behaviour has changed dramatically. Personal music collections have grown favoured by technological improvements in networks, storage, portability of devices and Internet services. This thesis presents the current methods used to recommend music assets, and reviews also some proposals of modelling user's musical preferences. Furthermore, the characterization of the music objects to be recommended is a complex task. This thesis studies the different facets of music knowledge management (based on editorial, cultural and acoustic metadata). This holistic approach allows to describe the different components of the music objects. These descriptions permit to enhance and improve music recommendations. Finally, the descriptions are enclosed into an ontological framework for semantic integration and retrieval of audiovisual metadata. As a test–bed example, two prototypes have been developed a music search engine and music discovery based on music similarity, and a hybrid music recommender. In both cases, the systems exploit and crawl music related content from the Web |
