Mining the CIA World Factbook

Abstract

Recent years have seen incredible advancements across a vast number of areas within Artificial Intelligence (AI). Such developments result in an increased use of Artificial Intelligence and Data Mining in order to obtain insight into several available data sets that can be utilised in order to draw conclusions from that information. The research involves the application of Data Mining techniques to the CIA World Factbook, a large data set covering a wide range of topics that is constantly updated by the CIA to ensure that the data remains up to date. This project takes a look at how Data Mining can be applied to this data set and analyses the results to see whether they are reflective of real-world situations through a number of Data Mining and Graph Analysis techniques, hence combining the fields of AI and International Relations. The first phase of the project is the Data Extraction phase. This process involves the extraction of data from the CIA World Factbook and placing it in a format more suited to the task at hand. These files are then mined for useful information and this information is, in turn, placed in a graph, where nodes represent countries and edges represents trading interactions between countries. This graph is then stored in a graph database. The second stage of the project is the Data Clustering phase, where algorithms are implemented in an attempt to divide the countries and territories contained within the CIA World Factbook into a number of clusters, using a number of different algorithms and representations of the data. This allows for the analysis of whether the clusters support real-world alliances and dependencies. The final stage is the Data Analysis stage. In this phase, some other analytical techniques are utilised in order to mine further results from the graph. These, along with the results from the previous phase, are then analysed in order to obtain a number of conclusions. This evaluation determines the ability of AI to reflect the state of the world and international relations despite the continuously shifting nature of current affairs. From the results obtained, the implemented algorithms have detected a number of alliances between countries, such as those between EU countries, has identified several countries dependant on trade with another, and determined the main global economic superpowers.