All Outputs (3)

Music recommendation: audio neighbourhoods to discover music in the long tail. (2015)
Presentation / Conference Contribution
CRAW, S., HORSBURGH, B. and MASSIE, S. 2015. Music recommendation: audio neighbourhoods to discover music in the long tail. In Hüllermeier, E. and Minor, M. (eds.) Proceedings of the 23rd international conference on case-based reasoning research and development (ICCBR 2015), 28-30 September 2015, Frankfurt am Main, Germany. Lecture notes in computer science, 9343. Cham: Springer [online], pages 73-87. Available from: https://doi.org/10.1007/978-3-319-24586-7_6

Millions of people use online music services every day and recommender systems are essential to browse these music collections. Users are looking for high quality recommendations, but also want to discover tracks and artists that they do not already... Read More about Music recommendation: audio neighbourhoods to discover music in the long tail..

Case-base maintenance with multi-objective evolutionary algorithms. (2015)
Journal Article
LUPIANI, E., MASSIE, S., CRAW, S., JUAREZ, J.M. and PALMA, J. 2016. Case-base maintenance with multi-objective evolutionary algorithms. Journal of intelligent information systems [online], 46(2), pages 259-284. Available from: https://doi.org/10.1007/s10844-015-0378-z

Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is critical to the problem-solvi... Read More about Case-base maintenance with multi-objective evolutionary algorithms..

Music recommenders: user evaluation without real users? (2015)
Presentation / Conference Contribution
CRAW, S., HORSBURGH, B. and MASSIE, S. 2015. Music recommenders: user evaluation without real users? In Yang, Q. and Woolridge, M. (eds.) Proceedings of the 24th International joint conference on artificial intelligence (IJCAI-15), 25-31 July 2015, Buenos Aires, Argentina. Palo Alto: AAAI Press [online], pages 1749-1755. Available from: https://www.ijcai.org/Proceedings/15/Papers/249.pdf

Good music recommenders should not only suggest quality recommendations, but should also allow users to discover new/niche music. User studies capture explicit feedback on recommendation quality and novelty, but can be expensive, and may have difficu... Read More about Music recommenders: user evaluation without real users?.