This thesis proposes an incremental algorithm to discover regional network access patterns from traffic data of a regional network. Because the size of network traffic database is very large, we need to develop a fast algorithm of association rules in order to efficiently generate user access patterns. Attributed relational graph is used to represent user access patterns on the network. The change of relational graph indicates the access pattern of a regional network is changed. In order to keep the network access pattern up to date without spending great computation costs, we propose an incremental procedure to generalize network access patterns from time to time. The results can be used for supporting network administrators to easily keep track of network usage patterns and better manage regional networks