Treffer: Efficient multi-feature index structures for music data retrieval

Title:
Efficient multi-feature index structures for music data retrieval
Source:
Storage and retrieval for media databases 2000 (San Jose CA, 26-28 January 2000)SPIE proceedings series. 3972:177-188
Publisher Information:
Bellingham WA: SPIE, 2000.
Publication Year:
2000
Physical Description:
print, 20 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, National Tsing Hua University, Hsinchu, 300, Tawain, Province of China
Rights:
Copyright 2001 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Sciences of information and communication. Documentation

FRANCIS
Accession Number:
edscal.779447
Database:
PASCAL Archive

Weitere Informationen

In this paper, we propose four index structures for music data retrieval. Based on suffix trees, we develop two index structures called Combined Suffix Tree and Independent Suffix Trees. These methods still show shortcomings for some search functions. Hence we develop another index, called Twin Suffix Trees, to overcome these problems. However, the Twin Suffix Trees lack of scalability when the amount of music data becomes large. Therefore we propose the fourth index, called Grid-Twin Suffix Trees, to provide scalability and flexibility for a large amount of music data. For each index, we can use different search functions, like exact search and approximate search, on different music features, like melody, rhythm or both. We compare the performance of the different search functions applied on each index structure by a series of experiments.