Majavu, WVan Zyl, TMarwala, T2009-03-262009-03-262008Majavu, 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 518-523978-1-4244-2808-3http://hdl.handle.net/10204/3250IEEE International GeoSciences and Remote Sensing Society (IGARSS) Symposium. Boston, Massachusetts, U.S.A., 6-11 July 2008Web 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 classificationenDocument clusteringLatent semantic indexingOntolgiesSensor webGeoSciencesWeb resident sensor resourcesRemote sensingConference PresentationMajavu, W., Van Zyl, T., & Marwala, T. (2008). Classification of web resident sensor resources using latent semantic indexing and ontologies. IEEE. http://hdl.handle.net/10204/3250Majavu, W, T Van Zyl, and T Marwala. "Classification of web resident sensor resources using latent semantic indexing and ontologies." (2008): http://hdl.handle.net/10204/3250Majavu 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 .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 -