Web-collaborative filtering: recommending music by crawling the Web
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
A music recommendation system based on music data grouping and user interests
Proceedings of the tenth international conference on Information and knowledge management
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
IEEE Intelligent Systems
Content-based music audio recommendation
Proceedings of the 13th annual ACM international conference on Multimedia
Inferring similarity between music objects with application to playlist generation
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
A music recommendation system based on music and user grouping
Journal of Intelligent Information Systems - Special issue: Intelligent multimedia applications
A probabilistic music recommender considering user opinions and audio features
Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
Scalable music recommendation by search
Proceedings of the 15th international conference on Multimedia
Towards ensemble learning for hybrid music recommendation
Proceedings of the 2007 ACM conference on Recommender systems
A hybrid social-acoustic recommendation system for popular music
Proceedings of the 2007 ACM conference on Recommender systems
Multimedia Tools and Applications
Mendeley - A Last.fm For Research?
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
An intelligent music playlist generator based on the time parameter with artificial neural networks
Expert Systems with Applications: An International Journal
Music recommendation based on acoustic features and user access patterns
IEEE Transactions on Audio, Speech, and Language Processing
Music Recommendation Using Content and Context Information Mining
IEEE Intelligent Systems
Music recommendation by unified hypergraph: combining social media information and music content
Proceedings of the international conference on Multimedia
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
JoMP: a mobile music player agent for joggers based on user interest and pace
IEEE Transactions on Consumer Electronics
Using structural information for distributed recommendation in a social network
Applied Intelligence
Dynamic adaptation of numerical attributes in a user profile
Applied Intelligence
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With rapid growth in the online music market, music recommendation has become an active research area. In most current approaches, content-based recommendation methods play an important role. Estimation of similarity between music content is the key to these approaches. A distance formula is used to calculate the music distance measure, and music recommendations are provided based on this measure. However, people have their own unique tastes in music. This paper proposes a method to calculate a personalized distance measure between different pieces of music based on user preferences. These methods utilize a randomized algorithm, a genetic algorithm, and genetic programming. The first two methods are based on Euclidean distance calculation, where the weight of each music feature in the distance calculation approximates user perception. The third method is not limited to Euclidean distance calculation. It generates a more complex distance function to estimate a user's music preferences. Experiments were conducted to compare the distance functions calculated by the three methods, and to compare and evaluate their performance in music recommendation.