عنوان مقاله
کشف جرم و شناسایی مجرم در هند با استفاده از تکنیک های داده کاوی
فهرست مطالب
مقدمه
پیشینه و کارهای مرتبط
روش
آزمایش و نتایج
نتیجه گیری
بخشی از مقاله
اجرای میانگینk CDCI
CDCI شرکا و روابط اصلی در داده های جرم مفروض را با استفاده از تکنیک های میانگین k و GMAPI جستجو می کند. این تکنیک ها کلیاتی از حجم وسیع داده های جرم فراهم نموده و روند جابجایی، جستجو، و بازیابی اطلاعات مطلوب جرم را تسهیل می نمایند. CDCI برای پیشگیری از جرم نیز می تواند مفید واقع شود.
کلمات کلیدی:
Crime detection and criminal identification in India using data mining techniques Devendra Kumar Tayal • Arti Jain • Surbhi Arora • Surbhi Agarwal • Tushar Gupta • Nikhil Tyagi Received: 15 July 2013 / Accepted: 10 March 2014 / Published online: 1 April 2014 Springer-Verlag London 2014 Abstract In the current paper, we propose an approach for the design and implementation of crime detection and criminal identification for Indian cities using data mining techniques. Our approach is divided into six modules, namely—data extraction (DE), data preprocessing (DP), clustering, Google map representation, classification and WEKA implementation. First module, DE extracts the unstructured crime dataset from various crime Web sources, during the period of 2000–2012. Second module, DP cleans, integrates and reduces the extracted crime data into structured 5,038 crime instances. We represent these instances using 35 predefined crime attributes. Safeguard measures are taken for the crime database accessibility. Rest four modules are useful for crime detection, criminal identification and prediction, and crime verification, respectively. Crime detection is analyzed using k-means clustering, which iteratively generates two crime clusters that are based on similar crime attributes. Google map improves visualization to k-means. Criminal identification and prediction is analyzed using KNN classification. Crime verification of our results is done using WEKA. WEKA verifies an accuracy of 93.62 and 93.99 % in the formation of two crime clusters using selected crime attributes. Our approach contributes in the betterment of the society by helping the investigating agencies in crime detection and criminals’ identification, and thus reducing the crime rates. Keywords Clustering Classification Crime Data mining Google map k-Means K-NN WEKA 1 Introdu
