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Association Rule - Spatial Data Mining Approach for Geo-Referenced in Crime to Crime Analysis

A. Thangavelu, S.R. Sathyaraj, R. Sridhar, S. Balasubramanian


Spatial data mining is a demanding field since huge amounts of spatial data that has been processed and turned into useful information by this paper. The increased crime rate and enormous amount of data being stored in crime databases by police personnel which has been collected from various jurisdiction of Coimbatore are gathered for the application of technologies which provides the means to turn data into information by data fusion and data mining. Data fusion organizes, combines and interprets information from multiple sources and it overcomes confusion from conflicting reports and cluttered or noisy backgrounds. Data mining is concerned with the automatic discovery of patterns and relationships with (crime to crime) in large databases. Technically, it is the process of finding correlations or patterns among dozens of fields in large relational databases using the tools of GIS. This paper 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.


Algorithm, Association Rule, Data Mining, Crime Data, GIS.

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