Implementation of conceptual graphs using frames in lead

  • K. C. Reddy
  • C. S. K. Reddy
  • P. G. Reddy
Knowledge Representation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 444)


This paper chiefly discusses the implementation of Sowa's Conceptual Graph notation using a frame-like data structure. Conceptual graphs serve as the basis for knowledge representation in our two systems, LEAD (Learning Expert system for Agricultural Domain) and XLAR (Universal Learning ARchitecture). The importance of conceptual graphs in knowledge representation is also briefly accounted for. Rationale for choosing frames for conceptual graph implementation is presented. Comparison of this implementation with other extant implementations is made.

Key Words

Knowledge Representation Conceptual Graphs Frames Semantic Nets Rules Learning Expert system 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [Barr, 1981]
    Barr, A., Feigenbaum, E.A., The Handbook of AI, vol.1, William Kaufmann Inc., 1981.Google Scholar
  2. [Barr and Feigenbaum, 1982]
    Barr, A., Feigenbaum, E.A., The Handbook of AI, vol.2, Addison Wesley, Reading, 1982.Google Scholar
  3. [Carbonnel et al., 1983]
    Carbonnel, J., Michalski, R. and Mitchell, T., Machine Learning: An AI Approach, ed. by R. Michalski, J. Carbonnel, T. Mitchell, Tioga Press, Palo Alto, CA, 1983.Google Scholar
  4. [Cersone and McCalla, 1983]
    Cersone, N., and McCalla, G., The Knowledge Frontier, ed. by Cercone, N., McCalla, G., Springer Verlag, NY, 1983.Google Scholar
  5. [Chan et al., 1988]
    Chan, Garner, B.J. and Tsui, E., Recursive Modal Unification for Reasoning with Knowledge using a Graph Representation, in Knowledge Base Systems, March,1988.Google Scholar
  6. [Clancey, 1985]
    Clancey, W.J., Heuristics Classification, Artificial Intelligence Intelligence, 27, 1985, pp. 289–350.Google Scholar
  7. [Cohen and Feigenbaum, 1982]
    Cohen, P.R., Feigenbaum, E.A., The Handbook of AI, vol.3, Addison Wesley, 1982.Google Scholar
  8. [CSReddy, 1989]
    C. S. Reddy. K., LEAD-1: Design and Implementation of a Knowledge Representation Scheme and a Proposal for a Learning Paradigm, M. Tech. Thesis, Univ. of Hyd., 1989Google Scholar
  9. [Duda et al., 1978]
    Duda, R.O., Hart, P.E., Nilson, N.J., Sutherland, G.L., Semantic Network Representation in Rule-based Inference Systems, in Pattern Directed Inference Systems, ed. by Waterman, D.A., Hayes-Roth, F., Academic Press,1978.Google Scholar
  10. [Fargues et al., 1986]
    Fargues, J., Landau, M.C., Dugourd, A., Catach, L., Conceptual Graphs for Semantics and Knowledge Processing, IBM Jr. of Research and Development 30, No.1, Jan. 1986.Google Scholar
  11. [Garner, 1985]
    Garner, B.J., Knowledge Representation for An Audit Office, Australian Computer Journal 17, No.3, Aug.1985.Google Scholar
  12. [Garner and Tsui, 1986]
    Garner, B.J., Tsui, E., An Extendible Graph Processor for Knowledge Engineering, SPIE Proceedings, vol.635, Application of AI III, Corlando, Florida, April, 1986.Google Scholar
  13. [Garner and Tsui, 1988]
    Garner, B.J., Tsui,E., General Purpose Inference Engine for Canonical Graph Models, Knowledge Based Systems, Dec.1988.Google Scholar
  14. [Jackman and Pavelin, 1988]
    Jackman, M., Pavelin, C., Conceptual Graphs, in Approaches to Knowledge Representation — An Introduction, ed. by Ringland, G.A., Duce, D.A., John Wiley & Sons Inc., NY,1988.Google Scholar
  15. [Minsky, 1975]
    Minski, M., A Framework for Representing Knowledge, in The Psychology of Computer Vision, ed. by P.H. Winston, McGraw-Hill, NY, 1975, pp.211–277.Google Scholar
  16. [Rangaswamy, 1984]
    Rangaswamy, G., Disease of Crop Plants in India, 2nd. ed., Prentice-Hall of India Pvt. Ltd. New Delhi, 1984.Google Scholar
  17. [Rao and Foo, 1987]
    Rao, A.S. and Foo, N.Y., Congres: Conceptual graph reasoning system, Proc. IEEE, 1987, pp.87–92.Google Scholar
  18. [Reddy and Reddy, 1986a]
    Reddy, K.C., Reddy, K.R.C., Advisory Expert systems in Plant Disease Diagnosis and Control, All India Seminar on Computer as a Tool for improving Agricultural Productivity, Hyderabad, India,1986.Google Scholar
  19. [Reddy et al., 1986b]
    Reddy, P.G., Reddy, K.C., Reddy, Y.B., Artificial Intelligence: Expert Systems Research: Adapting Technical Knowledge for Computer Based Agricultural Consultancy Systems, All India Seminar on Computer as a Tool for Improving Agricultural Productivity, Hyderabad, 1986.Google Scholar
  20. [Reddy, 1987]
    Reddy, K. C., Ph. D. Thesis Proposal, University of Hyderabad, Hyderabad, 1987.Google Scholar
  21. [Reddy et al., 1989]
    Reddy, K.C., C.S.Reddy.K, Reddy, P.G., LEAD: A Learning Expert System for Agricultural Diseases — Rice Diseases, accepted for International Conference on Applications of AI in Govt. and Industry, Hyderabad, 1989.Google Scholar
  22. [Sowa, 1976]
    Sowa, J.F., Conceptual Graphs for a Data Base Interface, IBM Jr. of Research and Dev. July 1976.Google Scholar
  23. [Sowa, 1984]
    Sowa, J.F., Conceptual Structures: Inf. Processing in Mind and Machine, Addison-Wesley, Reading, 1984.Google Scholar
  24. [Sowa and Way, 1986]
    Sowa, J.F. and Way, E., Implementing a Semantic Interpreter using Conceptual Graphs, IBM Jr. of Research and Dev., Jan. 1986.Google Scholar
  25. [Steel, 1984]
    Steele Jr., G.L., Common LISP, The Language, Digital Press, 1984.Google Scholar
  26. [Winston and Horn, 1981]
    Winston, P.H., Horn, B., LISP, Addison-Wesley, Reading, 1981.Google Scholar
  27. [Woods, 1987]
    Woods, W. A., What's Important About Knowledge Representation, in Knowledge Frontier, ed. Cercone, N., McCalla, G., Springer Verlag, NY 1987.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • K. C. Reddy
    • 1
  • C. S. K. Reddy
    • 1
  • P. G. Reddy
    • 1
  1. 1.School of Mathematics and Computer/Information SciencesUniversity of HyderabadHyderabadIndia

Personalised recommendations