Dynamic Minimum Support Incremental Frequent Trajectory Mining Algorithm

With the popularization of smart devices and the continuous development of wireless communication technology, a large amount of trajectory data is recorded in wireless networks, and frequent item mining for trajectory data has become a research hotspot. In order to update the frequent trajectory set when new data is added to the trajectory database and the minimum support is changed, we propose the dynamic minimum support incremental updating PrefixSpan algorithm (DMSIU-PrefixSpan). A method is proposed in the algorithm to estimate the support of a sequence, in which the confidence of its suffix subsequence is approximated to replace its own confidence when estimating the support of a sequence. With this method, the sequence support can be calculated without scanning the database. DMSIU-PrefixSpan algorithm can make full use of the information of frequent trajectory set. When incremental trajectory data is added to the original trajectory database and the minimum support changes, the candidate sequence is generated by connecting frequent trajectory sequence and frequent 1 sequence, and the candidate sequence support is estimated using the support estimation method to discover the frequent sequences. The algorithm no longer needs to save the original trajectory data and achieves fast update of the frequent trajectory set. The accuracy of the support degree estimation and the effectiveness of the algorithm of this paper are verified by the mining experiments of the trajectory database.