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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/3250

Title: Classification of web resident sensor resources using latent semantic indexing and ontologies
Authors: Majavu, W
Van Zyl, T
Marwala, T
Keywords: Document clustering
Latent semantic indexing
Ontolgies
Sensor web
GeoSciences
Web resident sensor resources
Remote sensing
Issue Date: 2008
Publisher: IEEE
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
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
Description: IEEE International GeoSciences and Remote Sensing Society (IGARSS) Symposium. Boston, Massachusetts, U.S.A., 6-11 July 2008
URI: http://hdl.handle.net/10204/3250
ISBN: 978-1-4244-2808-3
Appears in Collections:Sensor science and technology
General science, engineering & technology

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