Selection of concept detectors for video search by ontology-enriched semantic spaces

This paper describes the construction and utilization of two novel semantic spaces, namely Ontology-enriched Semantic Space (OSS) and Ontology-enriched Orthogonal Semantic Space (OS2), to facilitate the selection of concept detectors for video search. These two semantic spaces are enriched with onto...

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Main Authors: WEI, Xiao-Yong, NGO, Chong-wah, JIANG, Yu-Gang
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Language:English
Published: Institutional Knowledge at Singapore Management University 2008
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Online Access:https://ink.library.smu.edu.sg/sis_research/6342
https://ink.library.smu.edu.sg/context/sis_research/article/7345/viewcontent/itm08.pdf
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spelling sg-smu-ink.sis_research-73452021-11-23T04:06:48Z Selection of concept detectors for video search by ontology-enriched semantic spaces WEI, Xiao-Yong NGO, Chong-wah JIANG, Yu-Gang This paper describes the construction and utilization of two novel semantic spaces, namely Ontology-enriched Semantic Space (OSS) and Ontology-enriched Orthogonal Semantic Space (OS2), to facilitate the selection of concept detectors for video search. These two semantic spaces are enriched with ontology knowledge, while emphasizing consistent and uniform comparison of ontological relatedness among concepts for query-to-concept mapping. OS2, in addition to being a linear space like OSS, also guarantees orthogonality of the semantic space. Compared with other ontology reasoning measures, both spaces are capable of providing platforms that offer a global view of concept inter-relatedness, by allowing evaluation of concept similarity in metric spaces. We simulate OSS and OS2 by using LSCOM concepts and experiment search effectiveness with VIREO-374 concept detectors. Empirical observations indicate that the proposed semantic spaces enable more effective selection of concept detectors than eight other existing ontology measures. OS2, in particular, is better in providing a viable and reasonable solution for fusion of multiple concept detectors. 2008-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6342 info:doi/10.1109/TMM.2008.2001382 https://ink.library.smu.edu.sg/context/sis_research/article/7345/viewcontent/itm08.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Semantic space ontology concept-based video search semantic detectors Computer Sciences Graphics and Human Computer Interfaces
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Semantic space
ontology
concept-based video search
semantic detectors
Computer Sciences
Graphics and Human Computer Interfaces
spellingShingle Semantic space
ontology
concept-based video search
semantic detectors
Computer Sciences
Graphics and Human Computer Interfaces
WEI, Xiao-Yong
NGO, Chong-wah
JIANG, Yu-Gang
Selection of concept detectors for video search by ontology-enriched semantic spaces
description This paper describes the construction and utilization of two novel semantic spaces, namely Ontology-enriched Semantic Space (OSS) and Ontology-enriched Orthogonal Semantic Space (OS2), to facilitate the selection of concept detectors for video search. These two semantic spaces are enriched with ontology knowledge, while emphasizing consistent and uniform comparison of ontological relatedness among concepts for query-to-concept mapping. OS2, in addition to being a linear space like OSS, also guarantees orthogonality of the semantic space. Compared with other ontology reasoning measures, both spaces are capable of providing platforms that offer a global view of concept inter-relatedness, by allowing evaluation of concept similarity in metric spaces. We simulate OSS and OS2 by using LSCOM concepts and experiment search effectiveness with VIREO-374 concept detectors. Empirical observations indicate that the proposed semantic spaces enable more effective selection of concept detectors than eight other existing ontology measures. OS2, in particular, is better in providing a viable and reasonable solution for fusion of multiple concept detectors.
format text
author WEI, Xiao-Yong
NGO, Chong-wah
JIANG, Yu-Gang
author_facet WEI, Xiao-Yong
NGO, Chong-wah
JIANG, Yu-Gang
author_sort WEI, Xiao-Yong
title Selection of concept detectors for video search by ontology-enriched semantic spaces
title_short Selection of concept detectors for video search by ontology-enriched semantic spaces
title_full Selection of concept detectors for video search by ontology-enriched semantic spaces
title_fullStr Selection of concept detectors for video search by ontology-enriched semantic spaces
title_full_unstemmed Selection of concept detectors for video search by ontology-enriched semantic spaces
title_sort selection of concept detectors for video search by ontology-enriched semantic spaces
publisher Institutional Knowledge at Singapore Management University
publishDate 2008
url https://ink.library.smu.edu.sg/sis_research/6342
https://ink.library.smu.edu.sg/context/sis_research/article/7345/viewcontent/itm08.pdf
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