dc.contributor.author |
Majavu, W
|
|
dc.contributor.author |
Van Zyl, T
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|
dc.contributor.author |
Marwala, T
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|
dc.date.accessioned |
2009-03-26T13:41:56Z |
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dc.date.available |
2009-03-26T13:41:56Z |
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dc.date.issued |
2008 |
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dc.identifier.citation |
Majavu, W, Van Zyl, T and Marwala, T. 2008. Classification of web resident sensor resources using latent semantic indexing and ontologies. IEEE International GeoSciences and Remote Sensing Society (IGARSS) Symposium. Boston, Massachusetts, U.S.A., 6-11 July 2008, pp 518-523 |
en |
dc.identifier.isbn |
978-1-4244-2808-3 |
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dc.identifier.uri |
http://hdl.handle.net/10204/3250
|
|
dc.description |
IEEE International GeoSciences and Remote Sensing Society (IGARSS) Symposium. Boston, Massachusetts, U.S.A., 6-11 July 2008 |
en |
dc.description.abstract |
Web resident sensor resource discovery plays a crucial role in the realisation of the Sensor Web. The vision of the Sensor Web is to create a web of sensors that can be manipulated and discovered in real time. A current research challenge in the sensor web is the discovery of relevant web sensor resources. The proposed approach towards solving the discovery problem is to implement a modified Latent Semantic Indexing by making use of an Ontology for classifying Web Resident Resources found in geospatial web portals. The paper presents the use of Latent Semantic Indexing, an information retrieval mechanism, biased by combining Ontology concepts to the terms and objects, for improving the knowledge extraction from web resident documents. The use of an Ontology, before indexing of terms, to create a semantic link between documents with relevant content improves automatic content extraction and document classification |
en |
dc.language.iso |
en |
en |
dc.publisher |
IEEE |
en |
dc.subject |
Document clustering |
en |
dc.subject |
Latent semantic indexing |
en |
dc.subject |
Ontolgies |
en |
dc.subject |
Sensor web |
en |
dc.subject |
GeoSciences |
en |
dc.subject |
Web resident sensor resources |
en |
dc.subject |
Remote sensing |
en |
dc.title |
Classification of web resident sensor resources using latent semantic indexing and ontologies |
en |
dc.type |
Conference Presentation |
en |
dc.identifier.apacitation |
Majavu, W., Van Zyl, T., & Marwala, T. (2008). Classification of web resident sensor resources using latent semantic indexing and ontologies. IEEE. http://hdl.handle.net/10204/3250 |
en_ZA |
dc.identifier.chicagocitation |
Majavu, W, T Van Zyl, and T Marwala. "Classification of web resident sensor resources using latent semantic indexing and ontologies." (2008): http://hdl.handle.net/10204/3250 |
en_ZA |
dc.identifier.vancouvercitation |
Majavu W, Van Zyl T, Marwala T, Classification of web resident sensor resources using latent semantic indexing and ontologies; IEEE; 2008. http://hdl.handle.net/10204/3250 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Majavu, W
AU - Van Zyl, T
AU - Marwala, T
AB - Web resident sensor resource discovery plays a crucial role in the realisation of the Sensor Web. The vision of the Sensor Web is to create a web of sensors that can be manipulated and discovered in real time. A current research challenge in the sensor web is the discovery of relevant web sensor resources. The proposed approach towards solving the discovery problem is to implement a modified Latent Semantic Indexing by making use of an Ontology for classifying Web Resident Resources found in geospatial web portals. The paper presents the use of Latent Semantic Indexing, an information retrieval mechanism, biased by combining Ontology concepts to the terms and objects, for improving the knowledge extraction from web resident documents. The use of an Ontology, before indexing of terms, to create a semantic link between documents with relevant content improves automatic content extraction and document classification
DA - 2008
DB - ResearchSpace
DP - CSIR
KW - Document clustering
KW - Latent semantic indexing
KW - Ontolgies
KW - Sensor web
KW - GeoSciences
KW - Web resident sensor resources
KW - Remote sensing
LK - https://researchspace.csir.co.za
PY - 2008
SM - 978-1-4244-2808-3
T1 - Classification of web resident sensor resources using latent semantic indexing and ontologies
TI - Classification of web resident sensor resources using latent semantic indexing and ontologies
UR - http://hdl.handle.net/10204/3250
ER -
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en_ZA |