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Representation of highly-complex knowledge in a database

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Abstract

This paper presents a unified framework for representing highly-complex knowledge in a database as a new paradigm for handling large and complex information in an easy and efficient manner. The framework provides a database with the capabilities to support next generation databases for decision support systems through the use of derivation rules, temporal information, knowledge from multiple sources with different measures of quality and epistemic knowledge. The model integrates concepts from both thedatabase and theartificial intelligence disciplines.

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Authors and Affiliations

  1. Information Systems Engineering Group, Faculty of Industrial Engineering and Management, Technion-Israel Institute of Technology, 32000, Haifa, Israel

    Avigdor Gal & Opher Etzion

  2. Haas School of Business, University of California and Information & Computing Sciences Division, Lawrence Berkeley Laboratory, 94720, Berkeley, CA, USA

    Arie Segev

Authors
  1. Avigdor Gal
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  2. Opher Etzion
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  3. Arie Segev
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Gal, A., Etzion, O. & Segev, A. Representation of highly-complex knowledge in a database. J Intell Inf Syst 3, 185–203 (1994). https://doi.org/10.1007/BF00962978

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