DocumentCode :
480722
Title :
A Collaborative Model of Low-Level and High-Level Descriptors for Semantics-Based Music Information Retrieval
Author :
Wang, Jun ; Deng, Haojiang ; Yan, Qin ; Wang, JinLin
Author_Institution :
Inst. of Acoust., Chinese Acad. of Sci., Beijing
Volume :
1
fYear :
2008
fDate :
9-12 Dec. 2008
Firstpage :
532
Lastpage :
535
Abstract :
Although technologies of both low-level and high-level descriptors for music information retrieval (MIR) are advancing, there are some essential deficiencies while utilizing them separately. In this paper we propose a model where the low-level and high-level descriptors collaborate to support semantics-based MIR. The ontology of ldquomusic scenerdquo domain is constructed as a demonstration, and a set of domain related low-level and high-level descriptor analyses are introduced. Given the domain ontology and the analysis results as input, an abduction process is adopted to compute the semantics-based interpretations. Evaluations show that the collaborative model does not only give a better recall rate of semantics-based retrieval than separated models, but also maintains a promising precision meanwhile.
Keywords :
inference mechanisms; information retrieval; music; ontologies (artificial intelligence); semantic Web; vocabulary; Web-based feature; abduction process; collaborative model; domain ontology; high-level descriptor; low-level descriptor; music information retrieval; music scene domain; semantic-based MIR; semantic-based interpretation; Acoustics; Collaborative work; Data mining; Feature extraction; Intelligent agent; International collaboration; Layout; Music information retrieval; Ontologies; Web services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
Type :
conf
DOI :
10.1109/WIIAT.2008.27
Filename :
4740503
Link To Document :
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