SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Data structures and algorithms for nearest neighbor search in general metric spaces
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
Content-based organization and visualization of music archives
Proceedings of the tenth ACM international conference on Multimedia
When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
An industrial-strength content-based music recommendation system
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
Lightweight measures for timbral similarity of musical audio
Proceedings of the 1st ACM workshop on Audio and music computing multimedia
Psychoacoustics: Facts and Models
Psychoacoustics: Facts and Models
Scalable music recommendation by search
Proceedings of the 15th international conference on Multimedia
Nearest Neighbor Retrieval Using Distance-Based Hashing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
BoostMap: a method for efficient approximate similarity rankings
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Nonlinear dimensionality reduction for efficient and effective audio similarity searching
Multimedia Tools and Applications
Quantitative Analysis of a Common Audio Similarity Measure
IEEE Transactions on Audio, Speech, and Language Processing
MetricMap: an embedding technique for processing distance-based queries in metric spaces
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new metric for probability distributions
IEEE Transactions on Information Theory
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We present a filter-and-refine method to speed up nearest neighbor searches with the Kullback---Leibler divergence for multivariate Gaussians. This combination of features and similarity estimation is of special interest in the field of automatic music recommendation as it is widely used to compute music similarity. However, the non-vectorial features and a non-metric divergence make using it with large corpora difficult, as standard indexing algorithms can not be used. This paper proposes a method for fast nearest neighbor retrieval in large databases which relies on the above approach. In its core the method rescales the divergence and uses a modified FastMap implementation to speed up nearest-neighbor queries. Overall the method accelerates the search for similar music pieces by a factor of 10---30 and yields high recall values of 95---99% compared to a standard linear search.