As the volume of information augments, the importance of the Information Retrieval (IR) increases. Collaborative Information Retrieval (CIR) is one of the popular social-based IR approaches. A CIR system registers the previous user interactions to response to the subsequent user queries more efficiently. But the goals and the characteristics of two users may be different; so when they send the same query to a CIR system, they may be interested in two different lists of documents. In this paper we deal with the personalization problem in the CIR systems by constructing a profile for each user. We propose three new approaches to calculate the user profile similarity that we will employ in our personalized CIR algorithm.