CLUSTERED SPATIAL DATA MINING ASSOCIATION RULE TO EXPLORE LARGE VOLUMES OF RURAL CRIME

In this paper which interest to integrate a large volume of data setsinto useful information by adopting a various informationtechniques in the latest technology in world. The methodapproaches of Single variate Association Rule for Area to Crimebased on the knowledge discovery techniques such as, clusteringand association-rule mining. Data mining provides a clear findingto prevent from crime with associated to another crime occurrencewith the naked observation on correlation between one crime toanother crime. This tool is an autonomous pattern detector toreveal plausible cause-effect associations between layers of pointand area data. We present TATA algorithm with an exploratoryanalysis for the effectively explore geo-referenced data. We hopethis will lead to new approaches in the exploration of largevolumes of spatio-temporal data in crime model.