A Framework for Method-Specific Knowledge Compilation from Databases

  • Authors:

  • J. William Murdock;Ashok K. Goel;Michael J. Donahoo;Shamkant Navathe

  • Affiliations:

  • Intelligent Systems Group, College of Computing, Georgia Institute of Technology, Atlanta, GA 30332-0280, USA. murdock@cc.gatech.edu;Intelligent Systems Group, College of Computing, Georgia Institute of Technology, Atlanta, GA 30332-0280, USA. goel@cc.gatech.edu;School of Engineering and Computer Science, Baylor University, P.O. Box 97356, Waco, TX 76798-7356, USA. Jeff_Donahoo@baylor.edu;Database Systems Group, College of Computing, Georgia Institute of Technology, Atlanta, GA 30332-0280, USA. sham@cc.gatech.edu

  • Venue:
  • Journal of Intelligent Information Systems
  • Year:
  • 2001

Quantified Score

Hi-index 0.00

Visualization

Abstract

Generality and scale are important but difficult issues in knowledge engineering. At the root of the difficulty lie two challenging issues: how to accumulate huge volumes of knowledge and how to support heterogeneous knowledge and processing. One approach to the first issue is to reuse legacy knowledge systems, integrate knowledge systems with legacy databases, and enable sharing of the databases by multiple knowledge systems. We present an architecture called HIPED for realizing this approach. HIPED converts the second issue above into a new form: how to convert data accessed from a legacy database into a form appropriate to the processing method used in a legacy knowledge system. One approach to this reformed issue is to use method-specific compilation of data into knowledge. We describe an experiment in which a legacy knowledge system called INTERACTIVE KRITIK is integrated with an ORACLE database. The experiment indicates the computational feasibility of method-specific data-to-knowledge compilation.