In recent years, there has been a tremendous growth in the web and its usage, so much so that today many users find it difficult to get information that is relevant to them. This implies that there is a need to prioritize and try to get the information which the user is interested in. The behavior of the user is dynamic which makes it difficult to track his current interests and changes in his interests. If the user's interests are asked explicitly, most users tend to either ignore giving information or fill in wrong/incomplete information. Implicit user interested identification thus becomes imperative, which will not hamper his day-to-day web usage but the system learns about the users interests automatically, unobtrusively. This paper summarizes work done in the area of identifying user's interests implicitly through the actions performed by the user through his browser, while using the web. It also proposes measures to improve the efficiency of such systems by using a combinatorial approach.