A Novel Approach for Improving Results of Search Engine using Query Log, Support Factor and Clustering

Abstract

Enhancing the result standards of Web search and user experience, lately apprehended a lot of interest from the researchers. This paper intends to present a novel method for refining the search engine results corresponding to a user query. The proposed system makes the use of click through data to improve the present rankings of the Web pages and making it easier to distinguish the relevant Web pages from the irrelevant ones which would result in greater allegiance by the users. This is achieved by using the query log of a search engine. This paper provides a method to calculate the similarity of a query with the available Web pages and then cluster them accordingly. To achieve higher precision of results, the clusters are re-arranged once more.