A Meta Search Engine Approach for Organizing Web Search Results using Ranking and Clustering

The web is expanding with each passing day along with technological advancement in search engine. This results in a long list of links to be retrieved for any user query. However it is not possible to verify each link of this returned list. Even the use of page ranking algorithms in searching does not provide the desired results. To address the solution to this problem a new meta search engine is introduced that uses the similarity measurement function to determine the relevancy of web page with the given query and document clustering technique to group the results into different clusters.