Publication Type

Journal Article

Version

acceptedVersion

Publication Date

1-2009

Abstract

In this paper, we introduce a novel indexing scheme-query context tree (QUC-tree) to facilitate efficient query sensitive music search under different query contexts. Distinguished from the previous approaches, QUC-tree is a balanced multiway tree structure, where each level represents the data space at different dimensionality. Before the tree structure construction, principle component analysis (PCA) is applied for data analysis and transforming the raw composite features into a new feature space sorted by the importance of acoustic features. The PCA transformed data and reduced dimensions in the upper levels can alleviate suffering from dimensionality curse. To accurately mimic human perception, an extension called QUC +-tree is proposed, which further applies multivariate regression and EM based algorithm to estimate the weight of each individual feature. The comprehensive extensive experiments to evaluate the proposed structures against state-of-art techniques based on different datasets. The experimental results demonstrate the superiority of our technique.

Keywords

Indexing structure, KNN, QUC-tree, music, similarity query

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Publication

IEEE Transactions on Multimedia

Volume

11

Issue

2

First Page

313

Last Page

323

ISSN

1520-9210

Identifier

10.1109/TMM.2008.2009719

Publisher

IEEE

Additional URL

https://doi.org/10.1109/TMM.2008.2009719

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