Authors:
Madhur Garg
;
Jaspreet Singh
;
Jitesh Sachdeva
;
Harsh Mittal
and
Sanjay K. Dhurandher
Affiliation:
University of Delhi, India
Keyword(s):
Semantic Web, Search, Semantic Search, Semantic Page Ranking, Ontology Ranking.
Related
Ontology
Subjects/Areas/Topics:
Applications and Case-studies
;
Artificial Intelligence
;
Collaboration and e-Services
;
e-Business
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
The world is heading towards a phase of pure automation and artificial intelligence. In this context the science of exploring the possibility of computers interpreting the meanings of sentences is a topic of great interest. The search engines are in no way left behind from its impact. The prospects of having a semantic search engine that could explore the proper context of an input query and produce relevant results is being constantly looked for. In this backdrop we present our prototype – Aragog, which is even a step ahead than the conventional idea of a semantic search engine. This not only makes the user free from the hassle of browsing through hundreds of irrelevant results, but also generates results in an order that would match its intended context, with a high probability. The engine has been designed and tested in its nascent stage and the results have been found to be exemplary. Additionally, we have incorporated many other features such as synonym handling and explicit res
ult display that make it all the more tempting to emerge as the next generation’s search engine.
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