With an increasing continuous growth of information in WWW, it is very difficult to extract useful and relevant information from the huge amount of information. So, without any help on the system, the user may spend more time to get the interested information from the website. To solve above the problem, we proposed an approach for generating user interesting page (UIP) using weight value on web log data by associating with web usage mining techniques. Web usage mining, a classification of Web mining, is the application of data mining techniques to discover usage patterns from click stream data. This information can be exploited in various ways, such as enhancing the effectiveness of websites or developing directed web marketing campaigns. The goal of our system is to analyze user behaviours by mining enriched web access log data and create a top web page for the user with common needs or interests. This paper also focuses on to provide an overview how to generate frequent access pattern for the users from a Web log database without the use of domain specific ontology.