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Graph Database

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References

  1. Abiteboul S, Buneman P, Suciu D. Data on the Web: from relations to semistructured data and XML. San Francisco: Morgan Kaufmann; 2000.

    Google Scholar 

  2. Angles R, Gutiérrez C. Survey of graph database models. ACM Comput Surv. 2008;40(1):1–39.

    Article  Google Scholar 

  3. Baeza P. Querying graph databases. In: Proceedings of the 32nd ACM Symposium on Principles of Databases Systems; 2013. p. 175–88.

    Google Scholar 

  4. Buneman P, Davidson S, Fernandez M, Suciu D. Adding structure to unstructured data. In: Proceedings of the 6th International Conference on Database Theory; 1997. p.336–50.

    Google Scholar 

  5. Calvanese D, De Giacomo G, Lenzerini M, Vardi MY. Reasoning on regular path queries. SIGMOD Rec. 2003;32(4):83–92.

    Article  Google Scholar 

  6. Consens MP, Mendelzon AO. Hy+: a hygraph-based query and visualization system. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1993. p. 511–16.

    Google Scholar 

  7. Fernandez M, Suciu D. Optimizing regular path expressions using graph schemas. In: Proceedings of the 14th International Conference on Data Engineering; 1998. p. 14–23.

    Google Scholar 

  8. Giugno R, Shasha D. GraphGrep: a fast and universal method for querying graphs. In: Proceedings of the 16th International Conference on Pattern Recognition; 2002. p. 112–15.

    Google Scholar 

  9. Goldman R, Widom J. DataGuides: enabling query formulation and optimization in semistructured databases. In: Proceedings of the 23rd International Conference on Very Large Data Bases; 1997. p. 436–45.

    Google Scholar 

  10. Gyssens M, Paredaens J, Van den Bussche J, Van Gucht D. A graph-oriented object database model. IEEE Trans Knowl Data Eng. 1994;6(4):572–86.

    Article  Google Scholar 

  11. Harel D. On visual formalisms. Commun ACM. 1988;31(5):514–30.

    Article  MathSciNet  Google Scholar 

  12. He H, K Singh A. Graphs-at-a-time: query language and access methods for graph databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2008. p. 405–18.

    Google Scholar 

  13. Mendelzon AO, Wood PT. Finding regular simple paths in graph databases. SIAM J Comput. 1995;24(6):1235–258.

    Article  MathSciNet  MATH  Google Scholar 

  14. Mendelzon AO, Mihaila G, Milo T. Querying the World Wide Web. Int J Digit Libr. 1997;1(1): 54–67.

    Google Scholar 

  15. Milo T, Suciu D. Index structures for path expressions. In: Proceedings of the 7th International Conference on Database Theory; 1999. p. 277–95.

    Google Scholar 

  16. Olken F. Graph data management for molecular biology. OMICS: J Integr Biol. 2003;7(1):75–78.

    Article  Google Scholar 

  17. Picalausa F, Luo Y, Fletcher GHL, Hidders J, Vansummeren S. A structural approach to indexing triples. In: Proceedings of the 9th Extended Semantic Web Conference; 2012. p. 406–21.

    Google Scholar 

  18. Poulovassilis A, Levene M. A nested-graph model for the representation and manipulation of complex objects. ACM Trans Inf Syst. 1994;12(1):35–68.

    Article  Google Scholar 

  19. Sarwat M, Elnikety S, He Y, Kliot G. Horton: online query execution engine for large distributed graphs. In: Proceedings of the 28th International Conference on Data Engineering; 2012. p. 1289–292.

    Google Scholar 

  20. Sheth A, Aleman-Meza1 B, Budak Arpinar I, Bertram C, Warke Y, Ramakrishnan C, Halaschek C, Anyanwu K, Avant D, Sena Arpinar F, Kochut K. Semantic association identification and knowledge discovery for national security applications. J Database Manag. 2005;16(1):33–53.

    Article  MathSciNet  Google Scholar 

  21. Tompa FW. A data model for flexible hypertext database systems. ACM Trans Database Syst. 1989;7(1):85–100.

    Article  Google Scholar 

  22. Trißl S, Leser U. Fast and practical indexing and querying of very large graphs. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2007. p. 845–56.

    Google Scholar 

  23. Wood PT. Query languages for graph databases. SIGMOD Rec. 2012;41(1):50–60.

    Article  Google Scholar 

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Authors and Affiliations

  1. Birkbeck, University of London, London, UK

    Peter T. Wood

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  1. Peter T. Wood
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Correspondence to Peter T. Wood .

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Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

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Wood, P.T. (2018). Graph Database. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_183

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