Hybrid Technique Based on Clustering for Crime Detection in Data Mining
| Author(s) | : | Chhaya Narwariya, Dr. Shivnath Ghosh |
| Institution | : | M.E. (CSE), Maharana Pratap College of Technology Gwalior |
| Published In | : | Vol. 4, Issue 8 — August 2017 |
| Page No. | : | 440-446 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Crime Detection mainly performed in the Data Mining (DM) to detect the crime efficiently. Crimes are asocial annoyance and charge our society extremely in numerous behaviors. Any research that can facilitate in explainingcrimes quicker will pay for itself and regarding of this, there are many criminals commit. In the present paper, theyimplemented a procedure for the design and implementation of crime detection and criminal identification for Indiancities using DM techniques. Clustering is a most vital field of data analysis and data mining application. It is a set ofmethodologies for creating high superiority clusters and high intra-cluster similarity and low inter-class similarity. Inclustering, there is mixture of algorithms to break up the data into groups. K-means is the easiest and most frequentlyused algorithm for partitioning the data among the clustering algorithms in the field of scientific and industrial software.Fuzzy C-means clustering is utilized to amass the data into groups by characterizing certain degree. We used Fuzzy Cmeans and ACO in our proposed work to improve the crime detection rate of different cities.
Chhaya Narwariya, Dr. Shivnath Ghosh, “Hybrid Technique Based on Clustering for Crime Detection in Data Mining”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 8, pp. 440-446, August 2017.
