Knowledge models that are currently in-use for describing music metadata are insufficient to express the wealth of complex information about creative works, expressions, performances, publications, authors and performers. In this research, we aim to propose a method for structuring the classical music information coming from different heterogeneous librarian repositories. In particular, we research and implement an appropriate music ontology based on existing models, controlled vocabularies and tools for converting and visualizing the metadata. Moreover, we research how this data can be consumed by end-users, through the development of a web application for exploring the data and a recommendation system that takes advantage of the richness of the data.
Modeling, exploring and recommending music in its complexity
EKAW 2016, 20th International Conference on Knowledge Engineering and Knowledge Management, Doctoral Consortium Track, November 19-23, 2016, Bologna, Italy / Also published in Lecture Notes in Computer Science, Vol. 10180, Springer
Type:
Conférence
City:
Bologna
Date:
2016-11-19
Department:
Data Science
Eurecom Ref:
5057
Copyright:
© Springer. Personal use of this material is permitted. The definitive version of this paper was published in EKAW 2016, 20th International Conference on Knowledge Engineering and Knowledge Management, Doctoral Consortium Track, November 19-23, 2016, Bologna, Italy / Also published in Lecture Notes in Computer Science, Vol. 10180, Springer and is available at : http://dx.doi.org/10.1007/978-3-319-58694-6_41
See also:
PERMALINK : https://www.eurecom.fr/publication/5057
