Iterative Sub-Setting

Abstract

The objective of this document is to communicate the progress made on an initiative to improve the current Case-Based Reasoning (CBR) functionality of the Multi-Intelligence Tools Suite (MITS) platform. To do so, a new similarity measure based on information theory called Iterative Sub-Setting (ISS) is proposed. The goal of this initiative was to provide a potential solution to a list of issues identified in the literature about Maritime Anomaly Detection (MAD). Various tests with this measure were made to demonstrate the potential for it to address selected issues in MAD. Results show that this method is more sensible to the context where the CBR is performed, can be used with a small case base, evolve over time and provide an accurate confidence level on the selected cases.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2010
Accession Number
ADA545073

Entities

People

  • Etienne Martineau

Organizations

  • DRDC Valcartier

Tags

Communities of Interest

  • C4I
  • Counter WMD
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Anomaly Detection
  • Change Detection
  • Classification
  • Cognition
  • Data Mining
  • Data Science
  • Data Sets
  • Detection
  • Engineering
  • Identification Systems
  • Information Processing
  • Information Science
  • Information Theory
  • Machine Learning
  • National Security
  • Reasoning
  • Security

Fields of Study

  • Computer science

Readers

  • Approximation Theory.
  • Artificial Intelligence
  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.