Abstract
The simultaneous appearance patterns of reconnaissance targets (for short ‘SAPoRT’ latter) which are hided in large history data of the existing military intelligence surveillance and reconnaissance (ISR) system have significant merits on such situations as difficultly target identifying and joint reconnaissance warning. A new algorithm named FTAP-mine for mining SAPoRT was proposed in this paper, which is based on a novel data structure named FTAP-tree and a scheme of conditional search. The FTAP-tree can efficiently store large number of original target information to benefit the following mining process. The method of conditional search can efficiently narrow search space and improve efficiency of the presented algorithm. FTAP-mine employed the idea of pattern growth to recursively fetch frequent prefix patterns from the conditional pattern bases directly, and jointed the suffix to make a pattern growing. Simulation results show that FTAP-mine can efficiently discover frequent SAPoRT in reconnaissance data set and decrease its time complexity and space complexity simultaneously.
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