In this article, we present a new approach to page ranking. The page rank of a collection of Web pages can be represented in a parameterized model, and the user requirements can be represented by a set of constraints. For a particular parameterization, namely, a linear combination of the page ranks produced by different forcing functions, and user requirements represented by a set of linear constraints, the problem can be solved using a quadratic programming method. The solution to this problem produces a set of parameters which can be used for ranking all pages in the Web. We show that the method is suitable for building customized versions of PageRank which can be readily adapted to the needs of a vertical search engine or that of a single user.