Skip to main content
SpringerLink
Log in

HyperGraphDB: A Generalized Graph Database

  • Conference paper
Web-Age Information Management (WAIM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6185))

Included in the following conference series:

Abstract

We present HyperGraphDB, a novel graph database based on generalized hypergraphs where hyperedges can contain other hyperedges. This generalization automatically reifies every entity expressed in the database thus removing many of the usual difficulties in dealing with higher-order relationships. An open two-layered architecture of the data organization yields a highly customizable system where specific domain representations can be optimized while remaining within a uniform conceptual framework. HyperGraphDB is an embedded, transactional database designed as a universal data model for highly complex, large scale knowledge representation applications such as found in artificial intelligence, bioinformatics and natural language processing.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Angles, R., Gutierrez, C.: Survey of Graph Database Models. ACM Computing Surveys 40(1), Article 1 (2008)

    Google Scholar 

  2. Levene, M., Poulovassilis, A.: The Hypernode model and its associated query language. In: Proceedings of the 5th Jerusalem Conference on Information technology, pp. 520–530. IEEE Computer Society Press, Los Alamitos (1990)

    Google Scholar 

  3. Levene, M., Poulovassilis, A.: An object-oriented data model formalised through hypergraphs. Data Knowl. Eng. 6(3), 205–224 (1991)

    Google Scholar 

  4. Boley, H.: Directed recursive labelnode hypergraphs: A new representation-language. Artificial Intelligence 9(1) (1977)

    Google Scholar 

  5. Goertzel, B.: Patterns, Hypergraphs & Embodied General Intelligence. In: IEEE World Congress on Computational Intelligence, Vancouver, BC, Canada (2006)

    Google Scholar 

  6. Sheard, Tim: Languages of the Future. In: Proceedings of the ACM Conference on Object-Oriented Programming, Systems, Languages and Applications, Vancouver, British Columbia, Canada, (2004)

    Google Scholar 

  7. Klamt, S., Haus Utz-Uwe, Theis, F: Hypergraphs and cellular networks. PLoS Comput. Biol. 5(5) (2009)

    Google Scholar 

  8. Kok, S., Domingos, P.: Learning markov logic network structure via hypergraph lifting. In: Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, pp. 505–512. ACM, New York (2009)

    Google Scholar 

  9. Resource Description Framework, http://www.w3.org/RDF/

  10. RDF Semantics, http://www.w3.org/TR/rdf-mt/

  11. Carroll, J.J., Bizer, C., Hayes, P., Stickler, P.: Named graphs, provenance and trust. In: Proceedings of the 14th international conference on World Wide Web, WWW 2005, pp. 613–622. ACM, New York (2005)

    Google Scholar 

  12. Topic Maps, http://www.isotopicmaps.org/

  13. Berge, C.: Hypergraphs: combinatorics of finite sets. North-Holland, Amsterdam (1989)

    MATH  Google Scholar 

  14. Gallo, G., Long, G., Pallottino, S., Nguyen, S.: Directed hypergraphs and applications. Discrete Applied Mathematics 42(2-3), 177–201 (1993)

    Google Scholar 

  15. XML Schema, http://www.w3.org/XML/Schema

  16. Boley, H.: Declarative operations on nets. In: Lehmann, F. (ed.) Semantic Networks in Artificial Intelligence, pp. 601–637. Pergamon Press, Oxford (1992)

    Google Scholar 

  17. Aczel, P.: Non-well-founded sets. CSLI Lecture Notes, vol. 14. Stanford University, Center for the Study of Language and Information, Stanford, CA (1988)

    MATH  Google Scholar 

  18. Olson, M.A., Bostic, K., Seltzer, M.: Berkeley DB. In: Proceedings of the Annual Conference on USENIX Annual Technical Conference, p. 43. USENIX Association, Berkeley (1999)

    Google Scholar 

  19. IETF UUID draft specification, http://www.opengroup.org/dce/info/draft-leach-uuids-guids-01.txt

  20. Girard, J.-Y., Lafont, Y., Taylor, P.: Proofs and Types. Cambridge University Press, Cambridge (1989)

    MATH  Google Scholar 

  21. SPARQL Query Language for RDF, http://www.w3.org/TR/rdf-sparql-query/

  22. FIPA Agent Communication Language Specification, http://www.fipa.org/repository/aclspecs.html

  23. Searle, J.: Speech Acts. Cambridge University Press, Cambridge (1969)

    Book  Google Scholar 

  24. Miller, G.A.: WordNet: A Lexical Database for English. Communications of the ACM 38(11), 39–41 (1995)

    Article  Google Scholar 

  25. Sleator, D., Temperley, D.: Parsing English with a Link Grammar. Carnegie Mellon University Computer Science technical report CMU-CS-91-196 (1991)

    Google Scholar 

  26. RelEx Dependency Relationship Extractor, http://opencog.org/wiki/RelEx

  27. Morrison, J.P.: Flow-Based Programming: A New Approach to Application Development. Van Nostrand Reinhold, New York (1994)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Kobrix Software, Inc, USA

    Borislav Iordanov

Authors
  1. Borislav Iordanov
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, Australia

    Heng Tao Shen

  2. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  3. David R. Cheriton School of Computer Science, University of Waterloo, Canada

    M. Tamer Özsu

  4. Peking University, China

    Lei Zou

  5. Renmin University of China, China

    Jiaheng Lu

  6. National University of Singapore, Singapore

    Tok-Wang Ling

  7. Northeastern University, 110004, Shenyang, China

    Ge Yu

  8. College of Computer Science, Zhejiang University, 310027, Hangzhou, P.R. China

    Yi Zhuang

  9. University of Melbourne, Australia

    Jie Shao

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Iordanov, B. (2010). HyperGraphDB: A Generalized Graph Database. In: Shen, H.T., et al. Web-Age Information Management. WAIM 2010. Lecture Notes in Computer Science, vol 6185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16720-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-16720-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16719-5

  • Online ISBN: 978-3-642-16720-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation