User Manual and Installation Guide for the Graph Matching Toolkit (GMT) Version 1.0

Abstract

The intelligence community today is combating information overload. Analysts lack tools to extract relevant information from large masses of information. Graph-based algorithms can assist analysts to sift through vast amounts of information in order to find the subset relevant to a common intelligence picture. Graph-based tools can support social network analysis by facilitating the reasoning over relationships between actors and groups of actors. In order to address the challenge of information overload, researchers at the U.S. Army Research Laboratory developed the Graph Matching Toolkit (GMT). GMT is a visual interface for performing graph matching and serves as a front end to a variety of graph matching algorithms such as the Truncated Search Tree (TruST) algorithm. This report demonstrates the GMT interface and TruST algorithm in the context of performing a series of queries on the Ali Baba Data Set. Descriptions of key features and capabilities, as well as, step-by-step instructions for GMT use are provided. An extended use case suggests GMT is an effective tool for facilitating an analyst's search and social network analysis of a complex dataset to rapidly identify high-value targets (appendix A). An installation guide for GMT (appendix B) and technical support contact information (appendix C) are also included.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2014
Accession Number
ADA600703

Entities

People

  • Heather Roy
  • Kirk Ogaard
  • Sue Kase

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programs
  • Data Sets
  • Information Overload
  • Instructions
  • Intelligence Community
  • Manuals
  • Military Research
  • National Security
  • Operating Systems
  • Reasoning
  • Social Networks
  • Trees (Data Structures)
  • User Interface
  • User Manuals
  • Word Processors
  • Xml

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Instructional Design and Training Evaluation.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.