A Weighted Markov Model for Web Prefetching to Improve User Interface over Internet

Rapid growth of web application has increased the researcher’s interests in this era. All over the world has surrounded by the computer network. There is a very useful application call web application used for the communication and data transfer. An application that is accessed via a web browser over a network is called the web application. Web caching is a well-known strategy for improving the performance of Web based system by keeping Web objects that are likely to be used in the near future in location closer to user. The Web caching mechanisms are implemented at three levels: client level, proxy level and original server level. Significantly, proxy servers play the key roles between users and web sites in lessening of the response time of user requests and saving of network bandwidth. Therefore, for achieving better response time, an efficient caching approach should be built in a proxy server. This paper use FP growth, weighted rule mining concept and Markov model for fast and frequent web pre fetching in order to has improved the hit ratio of the web page and expedites users visiting speed.