Making a Graph Database from Unstructured Text

Abstract

From a huge volume of text of emails and SNS, it is required to extract human relations to determine whether or not there exist illegal connections each other. A graph structure becomes very useful for giving better representation of human relations compared with the original plain text. In this paper, we propose a way of constructing graph from a number of texts. To make the graph more concise and compact, it is also required to remove duplication and outliers in the graph. The key point of merging a graph structure is to perform automatic and semi-automatic merging method based on our novel merge-feasibility measurement. To justify our new methods of extracting and merging the graph structure, we describe the implementation and testing of our proposed system.