RDF Based Framework for Multi Image Retrieval using Semantic Web
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Abstract
Retrieving number of images from the Web, based on image content is a challenging field which is currently receiving lot of attention. The images of interest are retrieved from the database, based on the context query. The proposed model shows the architecture to integrate knowledge from dataset and semantic techniques. To extract the features like texture and color of images, we use semantic tools like Jena and Sparql Protocol and RDF Query Language (SPARQL). The model is developed using Resource Description Framework (RDF), where the initial search is based on keyword, then extended to knowledge based and SPARQL is used to retrieve relevant images from the corresponding RDF. The aim of the model is to explain the advantages of using Semantic Web languages and technologies to create, store, manipulate and process image metadata.
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Key Words: Jena, RDF, Semantic Techniques, Semantic Web, SPARQL
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