This paper shows how the gap between the texts based web pages and the Resource Descriptive Framework based pages of the semantic web can be bridged by ontologies. Most traditional search engines use indexes that are engineered at the syntactical level and come back hits based mostly on straightforward string comparisons or use the static keyword based indexing. However, the indexes don't contain synonyms, cannot differentiate between homonyms ('mouse' as a Pointing device vs. 'Mouse' as a living animal) and users receive completely different search results after they use different conjugation varieties of identical word. During this work, we have a tendency to gift a system that uses ontologies and Natural Language Processing techniques to construct index, and therefore supports word sense disambiguation. Therefore the retrieval of document that contains equivalent term as the context demands is achieved to provide efficient search engines through ontological indexing.

IR Indexing Semantic index Ontology Semantic search