The internet is very huge in size and increasing exponentially. Finding any relevant information from such a huge information source is now becoming very difficult. Millions of web pages are returned in response to a user's ordinary query. Displaying these web pages without ranking makes it very challenging for the user to find the relevant results of a query. This paper has proposed a novel approach that utilizes web content, usage, and structure data to prioritize web documents. The proposed approach has applications in several major areas like web personalization, adaptive website development, recommendation systems, search engine optimization, business intelligence solutions, etc. Further, the proposed approach has been compared experimentally by other approaches, WDPGA, WDPSA, and WDPII, and it has been observed that with a little trade off time, it has an edge over these approaches.