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Measuring concept similarities in multimedia ontologies: analysis and evaluations

Koskela, Markus and Smeaton, Alan F. and Laaksonen, J. (2007) Measuring concept similarities in multimedia ontologies: analysis and evaluations. IEEE Transactions on Multimedia, 9 (5). pp. 912-922. ISSN 1520-9210

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The recent development of large-scale multimedia concept ontologies has provided a new momentum for research in the semantic analysis of multimedia repositories. Different methods for generic concept detection have been extensively studied, but the question of how to exploit the structure of a multimedia ontology and existing inter-concept relations has not received similar attention. In this paper, we present a clustering-based method for modeling semantic concepts on low-level feature spaces and study the evaluation of the quality of such models with entropy-based methods. We cover a variety of methods for assessing the similarity of different concepts in a multimedia ontology. We study three ontologies and apply the proposed techniques in experiments involving the visual and semantic similarities, manual annotation of video, and concept detection. The results show that modeling inter-concept relations can provide a promising resource for many different application areas in semantic multimedia processing.

Item Type:Article (Published)
Uncontrolled Keywords:entropy; feature extraction; indexing; multimedia computing; ontologies (artificial intelligence); pattern clustering; semantic Web; video retrieval;
Subjects:Computer Science > Multimedia systems
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Research Initiatives and Centres > Adaptive Information Cluster (AIC)
Publisher:Institute of Electrical and Electronics Engineers
Official URL:
Copyright Information:Copyright © 2007 IEEE. Reprinted from IEEE Transactions on Multimedia. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Dublin City University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Funders:Irish Research Council for Science Engineering and Technology, Science Foundation Ireland, SFI 03/IN.3/I361, Academy of Finland
ID Code:251
Deposited On:07 Mar 2008 by DORAS Administrator. Last Modified 05 May 2010 11:21

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