基于关联规则挖掘的伴随车辆发现算法

ACCOMPANY VEHICLE DISCOVERY ALGORITHM BASED ON ASSOCIATION RULE MINING

伴随车辆是公安刑侦部门对海量车辆通行信息检索的一类实战需求,目的是通过模糊条件查询得到潜在的结伴作案车辆,究其本质,可将此类查询转化为数据挖掘中关联规则挖掘问题。通过对公路车辆智能监测记录系统采集的过车数据进行分析,将伴随车辆查询转化为关联规则挖掘,利用数据挖掘技术对过车数据查询问题进行综合分析,实现高效率的伴随车辆查询算法AVD(Accompany Vehicles D iscovery)。算法分析表明,AVD不但能提供准确的伴随车辆查询结果,而且效率高、扩展性强,具有较高的可行性。

Accompany vehicle query is a kind of practices need of police criminal investigation department with regard to massive vehicle traffic information retrieval,it is intended to acquire potential accompany committing vehicles through fuzzy condition query.And by studying its nature,such query can be transformed into association rules mining of data mining.In this paper,we convert the vehicle query to association rules mining by analysing passing vehicle data collected by smart highway traffics monitoring and recording system,make use of data mining technology to comprehensively analyse the passing vehicle data query,and realise the efficient accompany vehicles discovery（AVD） algorithm.It is shown in the section of algorithm analysis that the proposed algorithm AVD can provide precise outcomes of accompany vehicle query,and is also highly efficient,scalable,and with good practicability.