Abstract: An intelligent recommendation system is proposed based on clustering of Web user's navigation path.The system uses an architecture based on proxy techniques,and consists of two subsystems,i.e.,the offline subsystem,including data preparation and URL clustering based on user's browsing paths,and the online subsystem,including a recommendation engine and a Web HTTP server.A algorithm for generating recommendation rule set is proposed based on the user's browsing interest,which is measured by considering synthetically both the user's browsing time and the number of hits on the Web page.A recommendation algorithm is presented based on recommendation rule set and the length of Web site URLs.The experiments show that,comparing with the recommendation algorithms based on association rule or on user transaction,the algorithm precision is improved greatly.