With the increasing of data and Web users in the Internet, it is necessary and significant to identify users for offering further possible personalized services. To implement this goal, we used the users' surfing historical data stored in the Web log as features for classification. This paper aims to develop some techniques to achieve this objective using fuzzy neural networks (FNNs). Experimental results demonstrate the effectiveness of our proposed approach.