Search engines recommend queries to improve the satisfaction level of users by shortening
their search task. A proper solution for query recommendation is to analyze the users'
behaviors and mimic the query transition patterns adopted by different users who are
succeeded in finding their needed information. In this paper, we propose a novel three-layer
query recommendation method which is benefited from a query community graph in the first
layer. This graph is generated through clustering similar queries which tend to convey the …