World Wide Web is a huge repository of web pages and links. It provides abudance of information for the Internet users. Web mining is the use of Data mining frameworks to actually discover and concentrate data from web archives and administrations. Web mining is three sorts: Web use Mining, Web content Mining, and Web structure Mining. Web utilization mining is the process of finding information from the cooperation created by the clients in the types of access logs, program logs, intermediary server logs, client session information, treats. A huge amount of user request data is generated in a web log. Predicting user's requests based on previously visited pages is important for the web page recommendation, reduction of latency, and online advertising. The web server log document is naturally made and kept up by a server comprising of a rundown of exercises it performed. The proposed framework is intended for website page forecast in suggestion framework and also it is useful for the investigation of web mining calculation to get incessant consecutive access design from the web log document on the web server. After cleaning, and applying the longest common subsequence and Apriori algorithm, the outcomes of the effective calculation of web log access are inaccurate.