This paper describes our efforts to investigate factors in user browsing behavior to automatically evaluate Web pages that the user shows interest in. We developed a client site logging tool to monitor and log the user’s browsing behavior. We performed user experiment using ten participants to collect the browsing behavior, and evaluated the behaviors by performing classification learning using C4.5. We generated common user browsing behavior rules and evaluated these common rules against the individual participant data. This paper reports those findings.