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A framework to enable the semantic inferencing and querying of multimedia content

A framework to enable the semantic inferencing and querying of multimedia content Cultural institutions, broadcasting companies, academic, scientific and defence organisations are producing vast quantities of digital multimedia content. With this growth in audiovisual material comes the need for standardised representations encapsulating the rich semantic meaning required to enable the automatic filtering, machine processing, interpretation and assimilation of multimedia resources. Additionally generating high-level descriptions is difficult and manual creation is expensive although significant progress has been made in recent years on automatic segmentation and low-level feature recognition for multimedia. Within this paper we describe the application of semantic web technologies to enable the generation of high-level, domain-specific, semantic descriptions of multimedia content from low-level, automatically-extracted features. By applying the knowledge reasoning capabilities provided by ontologies and inferencing rules to large, multimedia data sets generated by scientific research communities, we hope to expedite solutions to the complex scientific problems they face. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Web Engineering and Technology Inderscience Publishers

A framework to enable the semantic inferencing and querying of multimedia content

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1476-1289
eISSN
1741-9212
Publisher site
See Article on Publisher Site

Abstract

Cultural institutions, broadcasting companies, academic, scientific and defence organisations are producing vast quantities of digital multimedia content. With this growth in audiovisual material comes the need for standardised representations encapsulating the rich semantic meaning required to enable the automatic filtering, machine processing, interpretation and assimilation of multimedia resources. Additionally generating high-level descriptions is difficult and manual creation is expensive although significant progress has been made in recent years on automatic segmentation and low-level feature recognition for multimedia. Within this paper we describe the application of semantic web technologies to enable the generation of high-level, domain-specific, semantic descriptions of multimedia content from low-level, automatically-extracted features. By applying the knowledge reasoning capabilities provided by ontologies and inferencing rules to large, multimedia data sets generated by scientific research communities, we hope to expedite solutions to the complex scientific problems they face.

Journal

International Journal of Web Engineering and TechnologyInderscience Publishers

Published: Jan 1, 2005

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