Comprehensive Query-Dependent Fusion Using Regression-on-Folksonomies: A Case Study of Multimodal Music Search

The combination of heterogeneous knowledge sources has been widely regarded as an effective approach to boost retrieval accuracy in many information retrieval domains. While various technologies have been recently developed for information retrieval, multimodal music search has not kept pace with th...

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Main Authors: ZHANG, Bingjun, Xiang, Qiaoliang, LU, Huanhuan, SHEN, Jialie, WANG, Ye
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Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/sis_research/480
http://dx.doi.org/10.1145/1631272.1631303
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-14792010-09-24T06:36:22Z Comprehensive Query-Dependent Fusion Using Regression-on-Folksonomies: A Case Study of Multimodal Music Search ZHANG, Bingjun Xiang, Qiaoliang LU, Huanhuan SHEN, Jialie WANG, Ye The combination of heterogeneous knowledge sources has been widely regarded as an effective approach to boost retrieval accuracy in many information retrieval domains. While various technologies have been recently developed for information retrieval, multimodal music search has not kept pace with the enormous growth of data on the Internet. In this paper, we study the problem of integrating multiple online information sources to conduct effective query dependent fusion (QDF) of multiple search experts for music retrieval. We have developed a novel framework to construct a knowledge space of users' information need from online folksonomy data. With this innovation, a large number of comprehensive queries can be automatically constructed to train a better generalized QDF system against unseen user queries. In addition, our framework models QDF problem by regression of the optimal combination strategy on a query. Distinguished from the previous approaches, the regression model of QDF (RQDF) offers superior modeling capability with less constraints and more efficient computation. To validate our approach, a large scale test collection has been collected from different online sources, such as Last.fm, Wikipedia, and YouTube. All test data will be released to the public for better research synergy in multimodal music search. Our performance study indicates that the accuracy, efficiency, and robustness of the multimodal music search can be improved significantly by the proposed folksonomy-RQDF approach. In addition, since no human involvement is required to collect training examples, our approach offers great feasibility and practicality in system development. 2009-10-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/480 info:doi/10.1145/1631272.1631303 http://dx.doi.org/10.1145/1631272.1631303 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University folksonomy multimodal search music query-dependent fusion Databases and Information Systems Numerical Analysis and Scientific Computing
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic folksonomy
multimodal search
music
query-dependent fusion
Databases and Information Systems
Numerical Analysis and Scientific Computing
spellingShingle folksonomy
multimodal search
music
query-dependent fusion
Databases and Information Systems
Numerical Analysis and Scientific Computing
ZHANG, Bingjun
Xiang, Qiaoliang
LU, Huanhuan
SHEN, Jialie
WANG, Ye
Comprehensive Query-Dependent Fusion Using Regression-on-Folksonomies: A Case Study of Multimodal Music Search
description The combination of heterogeneous knowledge sources has been widely regarded as an effective approach to boost retrieval accuracy in many information retrieval domains. While various technologies have been recently developed for information retrieval, multimodal music search has not kept pace with the enormous growth of data on the Internet. In this paper, we study the problem of integrating multiple online information sources to conduct effective query dependent fusion (QDF) of multiple search experts for music retrieval. We have developed a novel framework to construct a knowledge space of users' information need from online folksonomy data. With this innovation, a large number of comprehensive queries can be automatically constructed to train a better generalized QDF system against unseen user queries. In addition, our framework models QDF problem by regression of the optimal combination strategy on a query. Distinguished from the previous approaches, the regression model of QDF (RQDF) offers superior modeling capability with less constraints and more efficient computation. To validate our approach, a large scale test collection has been collected from different online sources, such as Last.fm, Wikipedia, and YouTube. All test data will be released to the public for better research synergy in multimodal music search. Our performance study indicates that the accuracy, efficiency, and robustness of the multimodal music search can be improved significantly by the proposed folksonomy-RQDF approach. In addition, since no human involvement is required to collect training examples, our approach offers great feasibility and practicality in system development.
format text
author ZHANG, Bingjun
Xiang, Qiaoliang
LU, Huanhuan
SHEN, Jialie
WANG, Ye
author_facet ZHANG, Bingjun
Xiang, Qiaoliang
LU, Huanhuan
SHEN, Jialie
WANG, Ye
author_sort ZHANG, Bingjun
title Comprehensive Query-Dependent Fusion Using Regression-on-Folksonomies: A Case Study of Multimodal Music Search
title_short Comprehensive Query-Dependent Fusion Using Regression-on-Folksonomies: A Case Study of Multimodal Music Search
title_full Comprehensive Query-Dependent Fusion Using Regression-on-Folksonomies: A Case Study of Multimodal Music Search
title_fullStr Comprehensive Query-Dependent Fusion Using Regression-on-Folksonomies: A Case Study of Multimodal Music Search
title_full_unstemmed Comprehensive Query-Dependent Fusion Using Regression-on-Folksonomies: A Case Study of Multimodal Music Search
title_sort comprehensive query-dependent fusion using regression-on-folksonomies: a case study of multimodal music search
publisher Institutional Knowledge at Singapore Management University
publishDate 2009
url https://ink.library.smu.edu.sg/sis_research/480
http://dx.doi.org/10.1145/1631272.1631303
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