Search engines are programs that search documents for specified keywords and return a list of the documents where the keywords were found. They return long list of ranked pages, finding the relevant information related to a particular topic is becoming increasingly critical and therefore, Search Result Optimization techniques come in to play. In this work an algorithm has been applied to recommend related queries to a query submitted by user. Query logs are important information repositories to keep track of user activities through the search results. Query logs contain attributes like query name, clicked URL, rank, time. Then the similarity based on Keyword and Clicked URL’s is calculated. Clusters have been obtained by combining the similarities of both keyword and clicked URL’s to perform query clustering. Most favored queries are discovered within every query cluster. The proposed result optimization system presents a query recommendation scheme towards better information retrieval to enhance search engine effectiveness to a large scale.