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

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Final technical rept. Jun 2000-Feb 2004

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Knowledge-Rich Acquisition of Knowledge from Experts Who Are Non-logicians KRAKEN was performed under DARPAs 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. KRAKENs 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 users context to display appropriate information, offer suitable choices of action, and interpret the users 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 others 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

Subject Categories:

  • Information Science
  • Computer Programming and Software

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