For weaknesses of a fixed structure and no personalization at the current remote education website, this paper uses the Web mining technology, extracts the server Web log of the website as the data source, finds the expected location of the target pages from the user access transaction sequences by using FEL and CRLL algorithm and generates the recommended link list according to the rule of minimal "Back" time, so the website can be changed according to the certain rule. This paper constructs a personalization Web system to predict Web page access and recommend contents by using user clusterin...
