  Intelligence analysts have long struggled with an abundance of data that must
be investigated on a daily basis. In the U.S. Army, this activity involves
reconciling information from various sources, a process that has been automated
to a certain extent, but which remains highly manual. To promote automation, a
semantic analysis prototype was designed to aid in the intelligence analysis
process. This tool, called Selective Plotting of Interconnected Data and Entity
Relations (SPIDER), extracts entities and their relationships from text in
order to streamline investigations. SPIDER is a web application that can be
remotely-accessed via a web browser, and has three major components: (1) a Java
API that reads documents, extracts entities and relationships using Stanford
CoreNLP, (2) a Neo4j graph database that stores entities, relationships, and
properties; (3) a JavaScript-based SigmaJS visualization tool for displaying
the graph on the browser. SPIDER can scale document analysis to thousands of
files for quick visualization, making the intelligence analysis process more
efficient, and allowing military leadership quicker insights into a vast array
of potentially-hidden knowledge.
