Accession Number:

ADA608627

Title:

Probabilistic Ontology Architecture for a Terrorist Identification Decision Support System

Descriptive Note:

Conference paper

Corporate Author:

EMSOLUTIONS INC ARLINGTON VA

Report Date:

2014-06-01

Pagination or Media Count:

30.0

Abstract:

Whether by nature or design, the personas of terrorists are often shrouded in mystery until they commit an act on the international stage. Without comment on the ethical dilemma that some identify with the practice, creating a profile of a terrorist from the available population serves as a starting point to reduce the volume of individuals requiring further investigation by limited analytic resources. A Terrorist Identification Probabilistic Ontology can assist the intelligence community in determining the likelihood of an individual being involved in terrorism using information about an individuals relations, group associations, communications, and background influences. Intelligence analysts may use the proposed decision support system to identify those individuals that bear further scrutiny and pose a risk to target countries or their interests. Using the Reference Architecture for Probabilistic Ontology Development as a blueprint, an architecture is instantiated to develop a Terrorist Identification Probabilistic Ontology used for decision support. Ontologies are a fundamental enabling technology for system interoperability. They provide machine-interpretable representation of domain semantics, thus allowing interchange of information with unambiguous, shared meaning. However, a fundamental aspect of many real-world problems is uncertainty, which traditional ontologies do not represent. Representation of uncertainty in real-world problems requires probabilistic ontologies, which integrate the inferential reasoning power of probabilistic representations with the first-order expressivity of ontologies. The Reference Architecture for Probabilistic Ontology Development RAPOD catalogues and defines the processes and artifacts necessary for the development, implementation and evaluation of explicit, logical and defensible probabilistic ontologies developed for knowledge-sharing and reuse in a given domain.

Subject Categories:

  • Information Science
  • Military Intelligence
  • Unconventional Warfare

Distribution Statement:

APPROVED FOR PUBLIC RELEASE