  Today's conventional search engines hardly do provide the essential content
relevant to the user's search query. This is because the context and semantics
of the request made by the user is not analyzed to the full extent. So here the
need for a semantic web search arises. SWS is upcoming in the area of web
search which combines Natural Language Processing and Artificial Intelligence.
The objective of the work done here is to design, develop and implement a
semantic search engine- SIEU(Semantic Information Extraction in University
Domain) confined to the university domain. SIEU uses ontology as a knowledge
base for the information retrieval process. It is not just a mere keyword
search. It is one layer above what Google or any other search engines retrieve
by analyzing just the keywords. Here the query is analyzed both syntactically
and semantically. The developed system retrieves the web results more relevant
to the user query through keyword expansion. The results obtained here will be
accurate enough to satisfy the request made by the user. The level of accuracy
will be enhanced since the query is analyzed semantically. The system will be
of great use to the developers and researchers who work on web. The Google
results are re-ranked and optimized for providing the relevant links. For
ranking an algorithm has been applied which fetches more apt results for the
user query.
