Pattern matching algorithms
Melodic matching techniques for large music databases
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Data mining: concepts and techniques
Data mining: concepts and techniques
A Survey of Longest Common Subsequence Algorithms
SPIRE '00 Proceedings of the Seventh International Symposium on String Processing Information Retrieval (SPIRE'00)
Computer Science in Perspective
An Evaluation System for Metrical Models
Computer Music Journal
Tree model of symbolic music for tonality guessing
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Comparison of classifier fusion methods for classification in pattern recognition tasks
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
New partially labelled tree similarity measure: a case study
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
A distance for partially labeled trees
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Classifying melodies using tree grammars
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
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Identifying copies or different versions of a same musical work is a focal problem in maintaining large music databases. In this paper we introduce novel ideas and methods that are applicable to metered, symbolically encoded polyphonic music. We show how to represent and compare polyphonic music using a tree structure. Moreover, we put for trial various comparison methods and observe whether better comparison results can be obtained by combining distinct similarity measures. Our experiments show that the proposed representation is adequate for the task with good quality results and processing times, and when combined with other methods it becomes more robust against various types of music.