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Approaching Semantically-Mediated Acoustic Data Fusion

Approaching Semantically-Mediated Acoustic Data Fusion
Approaching Semantically-Mediated Acoustic Data Fusion
Our primary hypothesis is that it should be possible to enrich data fusion by semantic processing, with wide potential application. In order to achieve our aim we need to represent the semantic data and enable reasoning about it in a framework that can be aligned with data fusion. Ontologies are most suited to this task as they allow for rich representation of data structure; some approaches include probabilistic representation. These can be aligned with data fusion approaches, such as Bayesian, which can fuse by including estimates of uncertainty. We shall describe our initial approaches towards establishing our hypothesis, including a survey of the enabling technologies, a description of application data (acoustic sensors, military scenario), and our new method of feature selection for acoustic data fusion. We also explore the semantic attributes and the representations that can be deployed for enrichment purposes, showing how ontologies can be used in this context. In these respects we shall show how we can approach enrichment of data fusion by semantic technologies, how this can capitalise on the current stock of techniques, and illustrate the potential benefits associated with this new approach.
Data Fusion, Semantic Web, Ontologies
Guo, Baofeng
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Wang, Yi
aa6a67f8-e22e-484d-8077-638d6c9b2f1a
Smart, Paul R
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Shadbolt, Nigel R
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Nixon, Mark S
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Damarla, Raju
173e7e77-3e54-4bcb-999b-bca7b1e4a529
Guo, Baofeng
e62b04c7-167b-45d9-a400-67a631861f24
Wang, Yi
aa6a67f8-e22e-484d-8077-638d6c9b2f1a
Smart, Paul R
cd8a3dbf-d963-4009-80fb-76ecc93579df
Shadbolt, Nigel R
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Nixon, Mark S
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Damarla, Raju
173e7e77-3e54-4bcb-999b-bca7b1e4a529

Guo, Baofeng, Wang, Yi, Smart, Paul R, Shadbolt, Nigel R, Nixon, Mark S and Damarla, Raju (2007) Approaching Semantically-Mediated Acoustic Data Fusion. Military Communications Conference (MILCOM), Orlando, Florida, United States. 29 - 31 Oct 2007.

Record type: Conference or Workshop Item (Paper)

Abstract

Our primary hypothesis is that it should be possible to enrich data fusion by semantic processing, with wide potential application. In order to achieve our aim we need to represent the semantic data and enable reasoning about it in a framework that can be aligned with data fusion. Ontologies are most suited to this task as they allow for rich representation of data structure; some approaches include probabilistic representation. These can be aligned with data fusion approaches, such as Bayesian, which can fuse by including estimates of uncertainty. We shall describe our initial approaches towards establishing our hypothesis, including a survey of the enabling technologies, a description of application data (acoustic sensors, military scenario), and our new method of feature selection for acoustic data fusion. We also explore the semantic attributes and the representations that can be deployed for enrichment purposes, showing how ontologies can be used in this context. In these respects we shall show how we can approach enrichment of data fusion by semantic technologies, how this can capitalise on the current stock of techniques, and illustrate the potential benefits associated with this new approach.

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More information

Published date: 2007
Additional Information: Event Dates: 29-31 October 2007
Venue - Dates: Military Communications Conference (MILCOM), Orlando, Florida, United States, 2007-10-29 - 2007-10-31
Keywords: Data Fusion, Semantic Web, Ontologies
Organisations: Vision, Learning and Control, Web & Internet Science

Identifiers

Local EPrints ID: 264735
URI: http://eprints.soton.ac.uk/id/eprint/264735
PURE UUID: e88a5244-ab9c-48c6-b9d1-86f404a366bd
ORCID for Paul R Smart: ORCID iD orcid.org/0000-0001-9989-5307
ORCID for Mark S Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 24 Oct 2007
Last modified: 15 Mar 2024 03:15

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Contributors

Author: Baofeng Guo
Author: Yi Wang
Author: Paul R Smart ORCID iD
Author: Nigel R Shadbolt
Author: Mark S Nixon ORCID iD
Author: Raju Damarla

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