Classification of web resident sensor resources using latent semantic indexing and ontologies

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