With the traveling records of browsers, one can analyze the preference of pages, further understand the demands of consumers, and promote the advertising and marketing. In this study, we use Maximum Forward Reference (MFR) algorithm to find the travel pattern of browsers from web logs. Simultaneously, experts are asked to evaluate the fuzzy importance weightings for different webs. At last, we employ fuzzy data mining technique that combines Apriori algorithm with fuzzy weights to determine the association rules. From the yielded association rules, one can be accurately aware of the information consumers need and which webs they prefer. This is important to governmental institutions and enterprises. Enterprises can find the commercial opportunities and improve the design of webs by means of this study. Governmental institutions can realize the needs of people from the obtained association rules, make the promotion of policy more efficiently, and provide better service quality.