In general different people have different search goals while searching in an engine. A search engine helps people reach their needed information. Click-through rate (CTR) is the ratio of users who click on a certain link to the total number of users who view a page. But on a broader concept it becomes difficult to actually tally each user’s query and give them the required solution. This paper here is to overcome the above problem. It is to conclude the user’s search goals by analyzing the search engine logs. Majorly the previous works try to fit in all user’ s search goal in a single way which is actually difficult because there is no guarantee that each user may have same search goals. The problem arises when the search goals of the users vary amongst one another and to overcome this here we use a framework model SEUC to mine the user preferences through feedback sessions. This will help in retrieval of information based on the user query. The feedback sessions are actually obtained by the click-through data of the user.