Abstract
In recent years, wireless networks and mobile applications grew rapidly. Mobile users not only request various kinds of interesting information, but also demand on the quality of services. In this p aper, we use an efficient algorithm called graph search technique (GST) to mine the frequent moving patterns of each mobile user. For found frequent moving patterns (FMPs), we further apply the Apriori algorithm to find the common FMPs among users. Finally, f or each group of users, a characterizing method is used to discover the relevant attribute values of the group. In the experiments, we observed that the GST algorithm has better performance in execution time and is more stable than the AprioriAll algorithm. Furthermore, we also observed the number of found patterns under different minimum support values and relevant percentages.
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