Ontology-enriched semantic space for video search

Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel fr...

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Main Authors: WEI, Xiao-Yong, NGO, Chong-wah
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2007
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Online Access:https://ink.library.smu.edu.sg/sis_research/6526
https://ink.library.smu.edu.sg/context/sis_research/article/7529/viewcontent/1291233.1291447.pdf
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spelling sg-smu-ink.sis_research-75292022-01-10T03:49:35Z Ontology-enriched semantic space for video search WEI, Xiao-Yong NGO, Chong-wah Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel framework for interpreting high-level semantics. In this paper, we propose a novel model, namely ontology-enriched semantic space (OSS), to provide a computable platform for modeling and reasoning concepts in a linear space. OSS enlightens the possibility of answering conceptual questions such as a high coverage of semantic space with minimal set of concepts, and the set of concepts to be developed for video search. More importantly, the query-to-concept mapping can be more reasonably conducted by guaranteeing the uniform and consistent comparison of concept scores for video search. We explore OSS for several tasks including conceptbased video search, word sense disambiguation and multimodality fusion. Our empirical findings show that OSS is a feasible solution to timely issues such as the measurement of concept combination and query-concept dependent fusion. 2007-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6526 info:doi/10.1145/1291233.1291447 https://ink.library.smu.edu.sg/context/sis_research/article/7529/viewcontent/1291233.1291447.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 Concept-based video search Ontology Semantic space Data Storage Systems 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 Concept-based video search
Ontology
Semantic space
Data Storage Systems
Graphics and Human Computer Interfaces
spellingShingle Concept-based video search
Ontology
Semantic space
Data Storage Systems
Graphics and Human Computer Interfaces
WEI, Xiao-Yong
NGO, Chong-wah
Ontology-enriched semantic space for video search
description Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel framework for interpreting high-level semantics. In this paper, we propose a novel model, namely ontology-enriched semantic space (OSS), to provide a computable platform for modeling and reasoning concepts in a linear space. OSS enlightens the possibility of answering conceptual questions such as a high coverage of semantic space with minimal set of concepts, and the set of concepts to be developed for video search. More importantly, the query-to-concept mapping can be more reasonably conducted by guaranteeing the uniform and consistent comparison of concept scores for video search. We explore OSS for several tasks including conceptbased video search, word sense disambiguation and multimodality fusion. Our empirical findings show that OSS is a feasible solution to timely issues such as the measurement of concept combination and query-concept dependent fusion.
format text
author WEI, Xiao-Yong
NGO, Chong-wah
author_facet WEI, Xiao-Yong
NGO, Chong-wah
author_sort WEI, Xiao-Yong
title Ontology-enriched semantic space for video search
title_short Ontology-enriched semantic space for video search
title_full Ontology-enriched semantic space for video search
title_fullStr Ontology-enriched semantic space for video search
title_full_unstemmed Ontology-enriched semantic space for video search
title_sort ontology-enriched semantic space for video search
publisher Institutional Knowledge at Singapore Management University
publishDate 2007
url https://ink.library.smu.edu.sg/sis_research/6526
https://ink.library.smu.edu.sg/context/sis_research/article/7529/viewcontent/1291233.1291447.pdf
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