With the increased confidence in the use of the Internet and the World Wide Web, the number of electronic commerce (e-commerce) transactions is growing rapidly. Therefore, finding useful patterns and rules of users’ behaviors has become the critical issue for e-commerce and can be used to tailor e-commerce services in order to successfully meet the customers’ needs. This paper proposes an approach to integrate Web content mining into Web usage mining. The textual content of web pages is captured through extraction of frequent word sequences, which are combined with Web server log files to discover useful information and association rules about users’ behaviors. The results of this approach can be used to facilitate better recommendation, Web personalization, Web construction, Website organization, and Web user profiling.