Extracting Theme Melodies by Using a Graphical Clustering Algorithm for Content-Based Music Information Retrieval

Kang, Yong-Kyoon; Ku, Kyong-I; Kim, Yoo-Sung

doi:10.1007/3-540-44803-9_8

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2010

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Cited by 4 publications

(3 citation statements)

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“…Kang, Ku, and Kim (2001) used a graphical clustering algorithm for extraction of melodic themes. Jones (1981) described uses of both Markov chains and grammars in music composition.…”

Section: Related Workmentioning

confidence: 99%

Machine Learning of Jazz Grammars

Gillick¹,

Tang

Keller

2010

Computer Music Journal

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“…Kang, Ku, and Kim (2001) used a graphical clustering algorithm for extraction of melodic themes. Jones (1981) described uses of both Markov chains and grammars in music composition.…”

Section: Related Workmentioning

confidence: 99%

Machine Learning of Jazz Grammars

Gillick¹,

Tang

Keller

2010

Computer Music Journal

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“…Based on the well-studied text, image and video data IR, music IR can be performed using text (metadata) [2], pieces of structured or unstructured music [6,16,23,41], humming [6,10,15,17,31] or even classic western musical notation [32] as queries.…”

Section: Work In Music Databasesmentioning

confidence: 99%

“…In [10] music melody and contour are mapped.Chen H. and Chen A.L.P. [12] focuses on properties such as pitch, duration and loudness, while [16,23,41] retain the melody of the music object.…”

Section: Work In Music Databasesmentioning

confidence: 99%

Finding maximum-length repeating patterns in music databases

Karydis

Νανόπουλος

Manolopoulos

2006

Multimed Tools Appl

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This paper introduces the problem of discovering maximum-length repeating patterns in music objects. A novel algorithm is presented for the extraction of this kind of patterns from a melody music object. The proposed algorithm discovers all maximum-length repeating patterns using an "aggressive" accession during searching, by avoiding costly repetition frequency calculation and by examining as few as possible repeating patterns in order to reach the maximum-length repeating pattern(s). Detailed experimental results illustrate the significant performance gains due to the proposed algorithm, compared to an existing baseline algorithm.

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A Content-Based Music Retrieval System Using Multidimensional Index of Time-Sequenced Representative Melodies from Music Database

Won

Park

et al. 2004

Advances in Databases and Information Systems

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Extracting Theme Melodies by Using a Graphical Clustering Algorithm for Content-Based Music Information Retrieval

Cited by 4 publications

References 5 publications

Machine Learning of Jazz Grammars

Machine Learning of Jazz Grammars

Finding maximum-length repeating patterns in music databases

A Content-Based Music Retrieval System Using Multidimensional Index of Time-Sequenced Representative Melodies from Music Database

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