Discovering fuzzy personal moving profiles in wireless networks

Wireless networks and mobile applications have grown very rapidly and have made a significant impact on computer systems. Especially, the usage of mobile phones and PDA is increased very rapidly. Added functions and values with these devices are thus greatly developed. If some regularity can be known from the user mobility behavior, then these functions and values can be further expanded and used intelligently. This paper thus attempts to discover fuzzy personal mobility patterns for helping systems provide personalized service in a wireless network. The arrival time and the duration time of each location area visited by a mobile user are used as important attributes in representing the results. Since both the arrival time and the duration time are numeric, fuzzy concepts are used to process them and to form linguistic terms. A fuzzy mining algorithm has then been proposed, which is based on the AprioriAll algorithm, but different from it in several ways. The difference causes a delicate consideration in the design of the algorithm. An example is also given to demonstrate the algorithm. The linguistic representation of personal mobility patterns will be more natural and understandable for the system managers to provide better personalized service in a wireless network.