Frequent pattern (FP) mining algorithms as the name says, mines sets FP form given datasets. These algorithms provide immensely helpful results which have a wide scope of application starting from simple decision problems to complex business intelligence aspects. This paper attempts to apply the same concept of FP mining to solve the location management problem of global system for mobile communication (GSM) networks. In GSM networks, the task of keeping track of a mobile user (MU) and relaying an incoming call is called location management. It basically includes two processes, location update, and paging. Location update deals with managing the current location of the MUs. There are many approaches to do this such as time based, movement based, and distance based. In this paper, the location update procedure relies on the collected data of user movements from one network cell to another cell. These data have a definite pattern, as in daily life a person mostly has a fixed route of traveling, e.g. home to office in the morning and office to home in the evening. During this movement, he crosses a specific set of network cells which remains same throughout the week. Thus, FP mining algorithm can be applied on the user's mobility log and try to find out the most probable location where the MU could be found. Using the results, a dynamic location area for individual user's current location can be created. Thus, minimizing cost related to location update which otherwise involves communication between the mobile handset and the base station, and calculations related to keeping track of the location of MUs.