Kraken-Knowledge Rich Acquisition of Knowledge from Experts Who Are Non-Logicians

Abstract

Knowledge-Rich Acquisition of Knowledge from Experts Who Are Non-logicians (KRAKEN) was performed under DARPA's Rapid Knowledge Formation (RKF) Program. The KRAKEN system allows Subject Matter Experts (SMEs) to more easily, efficiently, and correctly enter their knowledge into an artificial intelligence knowledge-based system. KRAKEN's usefulness has been demonstrated in three challenge problems related to molecular biology, authoring of course-of-action (CA) critiquing rules, and terrain analysis. This report contains a description of KRAKEN, a Knowledge Entry system developed as part of the Rapid Knowledge Formation Project, funded by DARPA. In addition to describing the KRAKEN system as it exists today, this report also discusses the development of the system, its performance in three annual evaluations, the lessons learnt that are of general interest to the community of knowledge entry systems developers, and specific insights for future research. The following are goals for the KRAKEN System: Rich Tools - the knowledge entry tools must themselves be knowledge-based; Multidimensional Context Tools - the system must model the user's context to display appropriate information, offer suitable choices of action, and interpret the user's action; Deeply Understand Text; Clarification and Discourse; Planning and Problem Solving; Explicit Reasoning about KE Methodology itself; KBs to fix KBs; Pegs3 - the NL understanding must be able to cope with anaphora and cataphora; Mix and Match - must be able to work within a heterogeneous array of different systems; Metaphors and Analogies - must be able to interpret metaphors, analogies, and similes; Active Collaboration Aid and Control - must support a collaborative mode of working whereby SMEs can share work and correct or review each other's work; Automated Tracking of Metrics; and Ultimate Impact - the system must provide a significant potential benefit to DoD and industry and institutions. (5 tables, 37 figures)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2004
Accession Number
ADA429360

Entities

People

  • Gavin Matthews
  • Jon Curtis
  • Kerry Hines
  • Pierluigi Miraglia
  • Robert C. Kahlert

Tags

Communities of Interest

  • C4I
  • Counter WMD
  • Engineered Resilient Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Artificial Intelligence
  • Chemistry
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computers
  • Geographic Information Systems
  • Information Systems
  • Knowledge Based Systems
  • Language
  • Molecular Biology
  • Natural Language Processing
  • Natural Languages
  • Ontologies
  • Urban Areas
  • Warfare

Readers

  • Artificial Intelligence

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Information Retrieval