CLUSTERED SPATIAL DATA MINING ASSOCIATION RULE TO EXPLORE LARGE VOLUMES OF RURAL CRIME
Journal Title: International Journal of Computer Science and Management Studies (IJCSMS) www.ijcsms.com - Year 2012, Vol 12, Issue 3
Abstract
In this paper which interest to integrate a large volume of data sets into useful information by adopting a various information techniques in the latest technology in world. The method approaches of Single variate Association Rule for Area to Crime based on the knowledge discovery techniques such as, clustering and association-rule mining. Data mining provides a clear finding to prevent from crime with associated to another crime occurrence with the naked observation on correlation between one crime to another crime. This tool is an autonomous pattern detector to reveal plausible cause-effect associations between layers of point and area data. We present TATA algorithm with an exploratory analysis for the effectively explore geo-referenced data. We hope this will lead to new approaches in the exploration of large volumes of spatio-temporal data in crime model.
Authors and Affiliations
Thangavelu A , Sathyaraj S. R , Syed Firdose , Krishnakeerthi Ch , Balasubramanian S
Keywords
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