Abstract: Advances in mobile communication and location determination technology have resulted in a mass of spatio temporal data of mobile users Moving sequential patterns mined from saptio temporal data effectively and efficiently can be used to enhance the performance of the mobile communication network and support decision making for location based services, intelligent transportation systems, etc However, with the rare network resources and massive mobile data, the traditional sequential pattern mining methods are not efficient enough An efficient project based algorithm, OSAF tree, is presented for moving sequential pattern mining This algorithm can get the maximal sequential patterns with one scan of databases and thereby is much more efficient What’s more, with a materialized OSAF tree structure, OSAF tree algorithm avoids scanning the database from scratch so that it supports interactive and incremental mining of moving sequential pattern with lower cost Experiments show that OSAF tree algorithm gains a great advantage over algorithms before