Abstract-Tremendous growth of the Web, lack of background knowledge about the Information Retrieval (IR), length of the input query keywords and its ambiguity, Query Recommendation is an important procedure which analyzes the real search intent of the user and recommends set of queries to be used in future to retrieve the relevant and required information. The proposed method recommends the queries by generating frequently accessed queries, rerank the recommended queries and evaluates the recommendation with the help of the ranking measures Normalized Discounted Cumulative Gain (NDCG) and Coefficient of Variance (CV). The proposed strategies are experimentally evaluated using real time American On Line (AOL) search engine query log.