Content area

Abstract

Over the past decade the number of images being captured and shared has grown enormously with the advent of the Internet as a medium of sharing resources like images, audio, video, documents etc., the Web users made it a way to interchange the knowledge as well. This behavior of the Web users over the Internet phenomenally turned the WWW into a huge repository of unstructured data inducing a need of the standard based representation of the data over the Internet. This need made itself more demanding because the searching or extraction of the knowledge from the unorganized data was becoming impossible, giving rise to the concept of Semantic Web. The use of XML for representing the data made the situation at the rest in the meanwhile. But, only the syntactical exploitation of the data could not help the situation because the process like searching of the images on the Web demanded the inclusion of the supplement of semantic structures into the list of standards. The Resource Description Framework (RDF) standard, a base technology of the Semantic Web, appeared as an intuitive solution of this problem as it employs the concept of annotation to describe the images and keeps all pieces of information pertaining to the images in the RDF documents, making the search process semantic rather than the traditional. In this paper, the intent is to generate annotated RDF model for semantic retrieval of images using RDF editor for annotation. This RDF model is validated through online W3C RDF validation service. SPARQL, RDF query engine, is used to query the validated RDF model to check the efficiency of image search. Key words: Resource description framework, RDF triples, RDFspecification, semantic web

Details

1009240
Location
Title
ENHANCING SEMANTIC WEB IMAGE SEARCH PRECISION
Volume
2
Issue
4
Publication year
2011
Publication date
Jul 2011
Section
Research Papers
Publisher
International Journal of Advanced Research in Computer Science
Place of publication
Udaipur
Country of publication
India
Publication subject
e-ISSN
09765697
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
ProQuest document ID
1443710096
Document URL
https://www.proquest.com/scholarly-journals/enhancing-semantic-web-image-search-precision/docview/1443710096/se-2?accountid=208611
Copyright
Copyright International Journal of Advanced Research in Computer Science Jul 2011
Last updated
2023-11-25
Database
ProQuest One Academic