ABSTRACT: Serial crimes are the problems which are mostly committed by minority of offenders. The law enforcement people are forced to find out the serial crimes which is considered as complex task. In order to find out the serial crimes, one need to investigate the large number of collected crimes which is unlinked with each other. These problem need to be analysed in different ways to find out the link among each crimes happened in various locations to find out serial crimes. In the previous work, cut clustering algorithm were used to cluster the similar type of crime happened in various locations .However the existing work lacks from the number of labelled classes used for clustering which will limit the number of data points to be used …show more content…
With the use of the computerized systems , computer data analysts have started helping the law enforcement officers and detectives to track crimes and to speed up the process of solving crimes. The detection of linked crimes is helpful to law enforcement for several reasons. Firstly, the collection of information from crime scenes increases the amount of available evidence. Secondly, the joint investigation of multiple crimes enables a more efficient use of law enforcement resources . Law enforcement needs to handle a large amount of reported, and the detection of series of crimes are often carried out manually. An integration of decision support system and GIS enable the law enforcement agencies to review the series of crimes in an efficient way. A geographic information system, is a computerized data management system which is used to capture, store, retrieve, analyze, and display spatial …show more content…
It is helpful for the law enforcement agencies to link the crime happened between different locations based upon the similarity coefficients such as spatial proximity, modus operandi etc has been detected and analysed.The serial crimes have been clustered by using incremental cut clustering algorithm efficiently and also class imbalance problem have been overcome in order to avoid the unnecessary clusters which results in high computation time.We have identified two aspects for future work. First, in this paper only individual edge representations have been investigated. Researchers have found that in some cases, combinations of edge representation scores have had a better performance than the individual edge representation. A distance index using combined crime characteristics, such as spatial and MO characteristics, needs to be developed.. Secondly an accuracy index that takes into account the imbalance of the data would be better suited than the Rand