This study adopts large access graph algorithm and case-base reasoning approach to generalize user access patterns and diagnose network events respectively for facilitating the network management. Large access graph (LAG) algorithm discovers the frequently inter-connections among hosts to provide an overview of network access relation. The case-based reasoning (CBR) system diagnoses the instant network events with the past experience. NetFlow log data collected from the router of the dormitory network of National Sun Yat-Sen University is used for demonstrating these two methods. The evaluation results measured by recall, precision, and accuracy show that these two mechanisms are useful to support the network administer to keep track of network access relations and diagnose the network events.