An approach to recommend pages to user after path completion

With the huge amount of data available on the web, the effective and timely search is most important aspects. Because of tremendous usage of web the size of the log files are becoming huge day by day. Web Mining which is an application of data mining can be used to improve web performance by generating patterns in the log files. Web Pre-fetching based on recommendation can be used to improve web performance. This paper proposes an architecture that recommends pages to the user based on studying the browsing activity of the user and other user of same usage profile and completing it in every aspects and then recommending the pages which can be pre-fetched to improve web performance. This paper proposes about the path completion which shows users interest and then recommending pages to the user which will result in effective recommendation.