Investigation and Analysis of New Approach of Intelligent Semantic Web Search Engines

AS WE KNOW THAT WWW IS ALLOWING PEOPLES TO SHARE THE HUGE INFORMATION GLOBALLY FROM THE BIG DATABASE REPOSITORIES. THE AMOUNT OF INFORMATION GROWS BILLIONS OF DATABASES. HENCE TO SEARCH PARTICULAR INFORMATION FROM THESE HUGE DATABASES WE NEED THE SPECIALIZED MECHANISM WHICH HELPS TO RETRIEVE THAT INFORMATION EFFICIENTLY. NOW DAYS VARIOUS TYPES OF SEARCH ENGINES ARE AVAILABLE WHICH MAKES INFORMATION RETRIEVING IS DIFFICULT. BUT TO PROVIDE THE BETTER SOLUTION TO THIS PROBLEM, SEMANTIC WEB SEARCH ENGINES ARE PLAYING VITAL ROLE. BASICALLY MAIN AIM OF THIS KIND OF SEARCH ENGINES IS TO PROVIDING THE REQUIRED INFORMATION IS SMALL TIME WITH MAXIMUM ACCURACY. BUT THE PROBLEM WITH SEMANTIC SEARCH ENGINES IS THAT THOSE ARE VULNERABLE WHILE ANSWERING THE INTELLIGENT QUERIES. THESE KINDS OF SEARCH ENGINES DON’T HAVE MUCH EFFICIENCY AS PER EXPECTATIONS BY END USERS, AS MOST OF TIME THEY ARE PROVIDING THE INACCURATE INFORMATION’S. THUS IN THIS PAPER WE ARE PRESENTING THE NEW APPROACH FOR SEMANTIC SEARCH ENGINES WHICH WILL ANSWER THE INTELLIGENT QUERIES ALSO MORE EFFICIENTLY AND ACCURATELY. WITH THE