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Querying Graph Databases: What Do Graph Patterns Mean?

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Conceptual Modeling (ER 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10650))

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Abstract

Querying graph databases often amounts to some form of graph pattern matching. Finding (sub-)graphs isomorphic to a given graph pattern is common to many graph query languages, even though graph isomorphism often is too strict, since it requires a one-to-one correspondence between the nodes of the pattern and that of a match. We investigate the influence of weaker graph pattern matching relations on the respective queries they express. Thereby, these relations abstract from the concrete graph topology to different degrees. An extension of relation sequences, called failures which we borrow from studies on concurrent processes, naturally expresses simple presence conditions for relations and properties. This is very useful in application scenarios dealing with databases with a notion of data completeness. Furthermore, failures open up the query modeling for more intricate matching relations directly incorporating concrete data values.

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Notes

  1. 1.

    https://www.w3.org/TR/rdf-sparql-query/.

  2. 2.

    https://neo4j.com/.

  3. 3.

    http://tinkerpop.apache.org/.

References

  1. Abriola, S., Barceió, P., Figueira, D., Figueira, S.: Bisimulations on data graphs. In: KR 2016, pp. 309–318. AAAI Press (2016)

    Google Scholar 

  2. Angles, R., Gutierrez, C.: Querying RDF data from a graph database perspective. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 346–360. Springer, Heidelberg (2005). doi:10.1007/11431053_24

    Chapter  Google Scholar 

  3. Brookes, S.D., Hoare, C.A.R., Roscoe, A.W.: A theory of communicating sequential processes. J. ACM 31(3), 560–599 (1984)

    Article  MathSciNet  Google Scholar 

  4. Brynielsson, J., Högberg, J., Kaati, L., Mårtenson, C., Svenson, P.: Detecting social positions using simulation. In: ASONAM 2010, pp. 48–55 (2010)

    Google Scholar 

  5. Fan, W.: Graph pattern matching revised for social network analysis. In: ICDT 2012, pp. 8–21. ACM, New York (2012)

    Google Scholar 

  6. Fan, W., Li, J., Ma, S., Tang, N., Wu, Y., Wu, Y.: Graph pattern matching: from intractable to polynomial time. PVLDB Endow. 3(1–2), 264–275 (2010)

    Article  Google Scholar 

  7. Gallagher, B.: Matching structure and semantics: a survey on graph-based pattern matching. In: Papers from the AAAI FS 2006, pp. 45–53 (2006)

    Google Scholar 

  8. van Glabbeek, R.J.: The linear time - branching time spectrum. In: Baeten, J.C.M., Klop, J.W. (eds.) CONCUR 1990. LNCS, vol. 458, pp. 278–297. Springer, Heidelberg (1990). doi:10.1007/BFb0039066

    Chapter  Google Scholar 

  9. Henzinger, M., Henzinger, T., Kopke, P.: Computing simulations on finite and infinite graphs. In: FOCS 1995, pp. 453–462. IEEE Computer Society (1995)

    Google Scholar 

  10. Imielinski, T., Lipski Jr., W.: Incomplete information in relational databases. J. ACM 31(4), 761–791 (1984)

    Article  MathSciNet  Google Scholar 

  11. Khan, A., Wu, Y., Aggarwal, C.C., Yan, X.: NeMa: fast graph search with label similarity. PVLDB Endow. 6(3), 181–192 (2013)

    Article  Google Scholar 

  12. Lee, J., Han, W.S., Kasperovics, R., Lee, J.H.: An in-depth comparison of subgraph isomorphism algorithms in graph databases. PVLDB Endow. 6(2), 133–144 (2012)

    Article  Google Scholar 

  13. Libkin, L., Martens, W., Vrgoč, D.: Querying graph databases with XPath. In: ICDT 2013, pp. 129–140. ACM, New York (2013)

    Google Scholar 

  14. Libkin, L., Martens, W., Vrgoč, D.: Querying graphs with data. J. ACM 63(2), 14:1–14:53 (2016)

    Article  MathSciNet  Google Scholar 

  15. Ma, S., Cao, Y., Fan, W., Huai, J., Wo, T.: Strong simulation: capturing topology in graph pattern matching. ACM Trans. Database Syst. 39(1), 4:1–4:46 (2014)

    Article  MathSciNet  Google Scholar 

  16. Motik, B., Horrocks, I., Sattler, U.: Bridging the gap between OWL and relational databases. In: WWW 2007, pp. 807–816. ACM, New York (2007)

    Google Scholar 

  17. Mottin, D., Lissandrini, M., Velegrakis, Y., Palpanas, T.: Exemplar queries: a new way of searching. VLDB J. 25(6), 741–765 (2016)

    Article  Google Scholar 

  18. Zheng, W., Zou, L., Lian, X., Wang, D., Zhao, D.: Efficient graph similarity search over large graph databases. IEEE Trans. Knowl. Data Eng. 27(4), 964–978 (2015)

    Article  Google Scholar 

  19. Zheng, W., Zou, L., Peng, W., Yan, X., Song, S., Zhao, D.: Semantic SPARQL similarity search over RDF knowledge graphs. PVLDB Endow. 9(11), 840–851 (2016)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Institut für Programmierung und Reaktive Systeme, TU Braunschweig, Braunschweig, Germany

    Stephan Mennicke

  2. Institut für Informationssysteme, TU Braunschweig, Braunschweig, Germany

    Jan-Christoph Kalo & Wolf-Tilo Balke

Authors
  1. Stephan Mennicke
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  2. Jan-Christoph Kalo
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  3. Wolf-Tilo Balke
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Corresponding author

Correspondence to Stephan Mennicke .

Editor information

Editors and Affiliations

  1. University of Klagenfurt, Klagenfurt, Austria

    Heinrich C. Mayr

  2. Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Giancarlo Guizzardi

  3. Victoria University of Wellington, Wellington, New Zealand

    Hui Ma

  4. Valencia University of Technology, Valencia, Spain

    Oscar Pastor

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Mennicke, S., Kalo, JC., Balke, WT. (2017). Querying Graph Databases: What Do Graph Patterns Mean?. In: Mayr, H., Guizzardi, G., Ma, H., Pastor, O. (eds) Conceptual Modeling. ER 2017. Lecture Notes in Computer Science(), vol 10650. Springer, Cham. https://doi.org/10.1007/978-3-319-69904-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-69904-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69903-5

  • Online ISBN: 978-3-319-69904-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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