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Meta-structural Graph-Based Design Patterns for Knowledge Representation in Association-Oriented Database Metamodel

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 720))

Abstract

This paper describes the problems of modeling graph-based structures in Association-Oriented Database Metamodel in the context of knowledge representation system. The basics of Association-Oriented Metamodel solutions, principles of modeling and sample implementations of graph structures have been presented, including labeled graphs as well as generalization of graphs, i.e. hypergraphs. Subsequently, metastructural ontological design patterns dedicated to knowledge representation systems are presented based on example of standard class-instance-feature-value and relationship patterns.

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Notes

  1. 1.

    By the term expressiveness authors understand the ability of language to express constructions and concepts of thought. It is a measure of phrases brevity in the language in relation to the complexity of the structure of thought, which it carries.

  2. 2.

    The standard of objects databases is OM ODMG 3.0.

References

  1. Collins, A.M., Quillian, M.R.: Retrieval time from semantic memory. J. Verbal Learn. Verbal Behav. 8, 240–247 (1969)

    Article  Google Scholar 

  2. Corcho, O., Gómez-Pérez, A.: A roadmap to ontology specification languages. In: International Conference on Knowledge Engineering and Knowledge Management, pp. 80–96 (2000). http://www.springerlink.com/index/QV8H33HQYB643Y14.pdf

  3. Dipert, R.R.: The mathematical structure of the world: the world as graph. J. Philos. 94(7), 329–358 (1997)

    MathSciNet  Google Scholar 

  4. Djedidi, R., Aufaure, M.A.: Ontology evolution: state of the art and future directions. In: Ontology Theory, Management and Design: Advanced Tools and Models, p. 179 (2010)

    Google Scholar 

  5. Fikes, R., Karp, P.D., Rice, J.P.: OKBC: a programmatic foundation for knowledge base interoperability. In: Proceedings of the National Conference on Artificial Intelligence, pp. 600–607 (1998). http://www.aaai.org/Library/AAAI/1998/aaai98-085.php

  6. Foxvog, D.: Cyc. In: Theory and Applications of Ontology: Computer Applications, pp. 259–278 (2010)

    Google Scholar 

  7. Genesereth, M.R., Fikes, R.E.: Knowledge Interchange Format, Version 3.0 Reference Manual. Interchange (Logic-92-1), pp. 1–68 (1992). http://logic.stanford.edu/kif/Hypertext/kif-manual.html

  8. Hoang, D.T.A., Priebe, T., Tjoa, A.M.: Hypergraph-based multidimensional data modeling towards on-demand business analysis. In: Proceedings of the 13th International Conference on Information Integration and Web-Based Applications and Services, pp. 36–43. ACM (2011)

    Google Scholar 

  9. Jodłowiec, M., Krótkiewicz, M.: Semantics discovering in relational databases by pattern-based mapping to association-oriented metamodel – a biomedical case study. In: Advances in Intelligent and Soft Computing. Springer, Cham (2016)

    Google Scholar 

  10. Krótkiewicz, M.: Association-oriented database model – n-ary associations. Int. J. Softw. Eng. Knowl. Eng. 27, 281 (2017)

    Article  Google Scholar 

  11. Krótkiewicz, M., Wojtkiewicz, K.: An introduction to ontology based structured knowledge base system: knowledge acquisition module. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) LNAI, vol. 7802, pp. 497–506 (2013)

    Google Scholar 

  12. Krótkiewicz, M., Wojtkiewicz, K., Jodłowiec, M., Pokuta, W.: Semantic knowledge base: quantifiers and multiplicity in extended semantic networks module, pp. 173–187. Springer, Cham (2016)

    Google Scholar 

  13. Liu, J.N.K., He, Y.L., Lim, E.H.Y., Wang, X.Z.: A new method for knowledge and information management domain ontology graph model. IEEE Trans. Syst. Man Cybern. Syst. 43(1), 115–127 (2013)

    Article  Google Scholar 

  14. Pancerz, K.: Some remarks on complex information systems over ontological graphs, pp. 377–384. Springer, Cham (2014)

    Google Scholar 

  15. Portmann, E., Kaltenrieder, P., Pedrycz, W.: Knowledge representation through graphs. Procedia Comput. Sci. 62, 245–248 (2015)

    Article  Google Scholar 

  16. Scioni, E., Hübel, N., Blumenthal, S., Shakhimardanov, A., Klotzbücher, M., Garcia, H., Bruyninckx, H.: Hierarchical hypergraphs for knowledge-centric robot systems: a composable structural meta model and its domain specific language NPC4. J. Softw. Eng. Robot. 7, 55–74 (2016)

    Google Scholar 

  17. Shadbolt, N., Hall, W., Berners-Lee, T.: The semantic web revisited. IEEE Intell. Syst. 21, 96–101 (2006)

    Article  Google Scholar 

  18. Sowa, J.F.: Conceptual graphs for a data base interface. IBM J. Res. Dev. 20(4), 336–357 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  19. Sowa, J.F.: Conceptual graphs. Found. Artif. Intell. 3, 213–237 (2008). (Findler 1979)

    Google Scholar 

  20. Speer, R., Havasi, C.: Representing general relational knowledge in ConceptNet 5. In: Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC 2012), pp. 3679–3686 (2012)

    Google Scholar 

  21. Trinkunas, J., Vasilecas, O.: A graph oriented model for ontology transformation into conceptual data model. Inf. Technol. Control 36(1), 126–132 (2007)

    Google Scholar 

  22. Vandenbussche, P.Y., Atemezing, G.A., Poveda-Villalón, M., Vatant, B.: Linked open vocabularies (LOV): a gateway to reusable semantic vocabularies on the Web. Semant. Web 8(3), 437–452 (2016). http://www.medra.org/servlet/aliasResolver?alias=iospress&doi=10.3233/SW-160213

    Article  Google Scholar 

  23. Welty, C.: Ontology research. AI Mag. 24(3), 11–12 (2003). http://www.aaai.org/ojs/index.php/aimagazine/article/view/1714/1612

    Google Scholar 

  24. Zhou, D., Huang, J., Schölkopf, B.: Learning with hypergraphs: clustering, classification, and embedding. In: Advances in Neural Information Processing Systems, vol. 19, pp. 1601–1608 (2007)

    Google Scholar 

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Correspondence to Marcin Jodłowiec .

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Jodłowiec, M., Krótkiewicz, M., Wojtkiewicz, K. (2018). Meta-structural Graph-Based Design Patterns for Knowledge Representation in Association-Oriented Database Metamodel. In: Hunek, W., Paszkiel, S. (eds) Biomedical Engineering and Neuroscience. BCI 2018. Advances in Intelligent Systems and Computing, vol 720. Springer, Cham. https://doi.org/10.1007/978-3-319-75025-5_18

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  • DOI: https://doi.org/10.1007/978-3-319-75025-5_18

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