Introducing Specialization and Generalization to a Graph-Based Data Model

  • Yuki Ohira
  • Teruhisa Hochin
  • Hiroki Nomiya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6884)


This paper proposes the schema graph for introducing specialization and generalization to a graph-based data model in order to systematize and reuse knowledge effectively. Systematizing and reusing knowledge are important functions of the knowledge-based human activity. The schema graph enables specialization and generalization relationships to be dynamically added, and removed. The methods of modifying these relationships are precisely presented. The schema graph enables us to systematize and reuse knowledge with keeping the structure flexible.


Semantic Network Content Representation Ball Game Schema Graph Instance Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Petrakis, E.G.M., Faloutsos, C.: Similarity Searching in Medical Image Databases. IEEE Trans. on Know. and Data Eng. 9, 435–447 (1997)CrossRefGoogle Scholar
  2. 2.
    Uehara, K., Oe, M., Maehara, K.: Knowledge Representation, Concept Acquisition and Retrieval of Video Data. In: Proc. of Int’l Symposium on Cooperative Database Systems for Advanced Applications, pp. 218–225 (1996)Google Scholar
  3. 3.
    Jaimes, A.: A Component-Based Multimedia A Data Model. In: Proc. of ACM Workshop on Multimedia for Human Communication: from Capture to Convey (MHC 2005), pp. 7–10 (2005)Google Scholar
  4. 4.
    Manjunath, B.S., Salembier, P., Sikora, T. (eds.): Introduction to MPEG-7. John Wiley & Sons, Ltd., Chichester (2002)Google Scholar
  5. 5.
    Hochin, T.: Graph-based data model for the content representation of multimedia data. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds.) KES 2006. LNCS (LNAI), vol. 4252, pp. 1182–1190. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Hochin, T., Nomiya, H.: A Logical and Graphical Operation of a Graph-based Data Model. In: Proc. of 8th IEEE/ACIS Int’l Conference on Computer and Information Science (ICIS 2009), pp. 1079–1084 (2009)Google Scholar
  7. 7.
    Hochin, T.: Decomposition of Graphs Representing the Contents of Multimedia Data. Journal of Communication and Computer 7(4), 43–49 (2010)Google Scholar
  8. 8.
    Smith, J.M., Smith, D.C.P.: Database abstractions: Aggregation and generalization. ACM Trans. Database Syst. 2(2), 105–133 (1977)CrossRefGoogle Scholar
  9. 9.
    Silberschatz, A., Korth, H., Sudarshan, S.: Database System Concepts, 4th edn. McGraw Hill, New York (2002)zbMATHGoogle Scholar
  10. 10.
    Abiteboul, S., Hull, R.: IFO: A Formal Semantic Database Model. ACM Transactions on Database Systems 12(4), 525–565 (1987)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Tanaka, K., Nishio, S., Yoshikawa, M., Shimojo, S., Morishita, J., Jozen, T.: Obase Object Database Model: Towards a More Flexible Object-Oriented Database System. In: Proc. of Int’l. Symp. on Next Generation Database Systems and Their Applications (NDA 1993), pp. 159–166 (1993)Google Scholar
  12. 12.
    Sowa, J.F.: Conceptual Structures - Information Processing in Mind and Machine. Addison-Wesley, Reading (1984)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yuki Ohira
    • 1
  • Teruhisa Hochin
    • 1
  • Hiroki Nomiya
    • 1
  1. 1.Kyoto Institute of TechnologyKyotoJapan

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