An Outlier-based Data Association Method For Linking Criminal Incidents

摘要

Data association is an important data mining task and it has various applications. In crime analysis, data association means linking criminal incidents committed by the same person. It helps to discover crime patterns and catch the criminals. In this paper, we present an outlier-based data association method. An outlier score function is defined to measure the extremeness of an observation, and a data association method is developed based upon the outlier score function. We applied this method to the robbery data in Richmond, Virginia, and compared the result with a similarity-based association method. The results show that the outlier-based data association method is promising.