A Detailed Survey on Crime Detecting and Clustering Technique in Data Mining

Authors

  • Chhaya Narwariya
  • Dr. Shivnath Ghosh

DOI:

https://doi.org/10.37591/joadms.v4i2.1050

Abstract

Abstract

Data mining is the extraction of useful information or the knowledge from the set of data or it’s the process analyzing the data from the various perspectives and summarizing into information which is useful. Detection of crime begins with discovery of crime scene, and proceeds from side to side the process of evidence collected works, identification and the analysis. It is called as an act that is being committed or being omitted in the infringement of law forbidding or the commanding it and which punishment is the compulsory upon the promise. This paper compares, categorizes and summarizes from almost all published in the technological and review articles in automatic type of scam discovery in last ten years. It gives   formalizes, professional fraudster the types of main and the types of the known fraud, and presents nature of the data evidence that is collected within the industries those are affected. Within business context of the   extracting the data to achieve the higher amount of cost savings, this research shows methods and approaches together with their issues.

Keywords: Data mining, Crime detection, Fraud maching,  K-means clustering, Artificial Neural Network

Cite this Article

Chhaya Narwariya, Dr. Shivnath Ghosh. A Detailed Survey on Crime Detecting and Clustering Technique in Data Mining. Journal of Advanced Database Management & Systems. 2017; 4(2):    19–26p.

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Published

2017-08-07

Issue

Vol. 4 No. 2 (2017)

Section

Research Articles

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