GLOBAL TERRORISM DATABASE ANALYSIS AND CLASSIFICATION

Abstract

In this project we implement a software which is capable of analyzing the data from GTD (global terrorism database). This software will tell about the data already present in GTD and by analyzing this data it will generate a completely new data set or information not known before. This project is a text mining project which will use naïve Bayes classification algorithm. The technologies (Tools) we have used in our project are C#.Net, SQL Server Database, R-Studio and Microsoft Excel (for presenting the data). Our actual task is to take the summary of each record of crime and identify that which type of crime it is. We have about 46000 valid records in our database so as a rule of thumb of naïve Bayes algorithm, we will divide them into two sets of which one will be called training data set and the other one, testing data set. We will manage the required information by ourselves in training data set and this information would be fed into the software from which it will learn and generate a structure which will help in getting the required information in testing data set.