Skip to main content

Vadalog: Recent Advances and Applications

  • Conference paper
  • First Online:
Logics in Artificial Intelligence (JELIA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11468))

Included in the following conference series:

Abstract

Vadalog is a logic-based reasoning language for modern AI applications, in particular for knowledge graph systems. In this paper, we present recent advances and applications, with a focus on the Vadalog language itself. We first give an easy-to-access self-contained introduction to Warded Datalog+/−, the logical core of Vadalog. We then discuss some recent advances: Datalog rewritability of Warded Datalog+/−, and the piece-wise linear fragment of Warded Datalog+/− that achieves space efficiency. We then proceed with some recent practical applications of the Vadalog language: detection of close links in financial knowledge graphs, as well as the detection of family-owned businesses.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

References

  1. Guideline (EU) 2018/570 of the ECB. https://www.ecb.europa.eu/ecb/legal/pdf/celex_32018o0003_en_txt.pdf (2018). Accessed 04 Mar 2019

  2. Afrati, F.N., Gergatsoulis, M., Toni, F.: Linearisability on datalog programs. Theor. Comput. Sci. 308(1–3), 199–226 (2003)

    Article  MathSciNet  Google Scholar 

  3. Arenas, M., Gottlob, G., Pieris, A.: Expressive languages for querying the semantic web. ACM Trans. Database Syst. 43(3), 13:1–13:45 (2018)

    Article  MathSciNet  Google Scholar 

  4. Arming, S., Pichler, R., Sallinger, E.: Complexity of repair checking and consistent query answering. In: ICDT, pp. 21:1–21:18 (2016)

    Google Scholar 

  5. Bellomarini, L., Fakhoury, D., Gottlob, G., Sallinger, E.: Knowledge graphs and enterprise AI: the promise of an enabling technology. In: ICDE (2019)

    Google Scholar 

  6. Bellomarini, L., et al.: Data science with Vadalog: bridging machine learning and reasoning. In: Abdelwahed, E.H., Bellatreche, L., Golfarelli, M., Méry, D., Ordonez, C. (eds.) MEDI 2018. LNCS, vol. 11163, pp. 3–21. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00856-7_1

    Chapter  Google Scholar 

  7. Bellomarini, L., Gottlob, G., Pieris, A., Sallinger, E.: Swift logic for big data and knowledge graphs. In: IJCAI, pp. 2–10 (2017)

    Google Scholar 

  8. Bellomarini, L., Sallinger, E., Gottlob, G.: The Vadalog system: datalog-based reasoning for knowledge graphs. PVLDB 11(9), 975–987 (2018)

    Google Scholar 

  9. Berger, G., Gottlob, G., Pieris, A., Sallinger, E.: The space-efficient core of Vadalog. In: PODS (2019, to appear)

    Google Scholar 

  10. Bertossi, L.E., Gottlob, G., Pichler, R.: Datalog: bag semantics via set semantics. In: ICDT (2019, to appear)

    Google Scholar 

  11. Calì, A., Gottlob, G., Kifer, M.: Taming the infinite chase: query answering under expressive relational constraints. J. Artif. Intell. Res. 48, 115–174 (2013)

    Article  MathSciNet  Google Scholar 

  12. Csar, T., Lackner, M., Pichler, R., Sallinger, E.: Winner determination in huge elections with MapReduce. In: AAAI, pp. 451–458 (2017)

    Google Scholar 

  13. Fagin, R., Kolaitis, P.G., Miller, R.J., Popa, L.: Data exchange: semantics and query answering. Theor. Comput. Sci. 336(1), 89–124 (2005)

    Article  MathSciNet  Google Scholar 

  14. Fayzrakhmanov, R.R., Sallinger, E., Spencer, B., Furche, T., Gottlob, G.: Browserless web data extraction: challenges and opportunities. In: WWW, pp. 1095–1104 (2018)

    Google Scholar 

  15. Furche, T., Gottlob, G., Neumayr, B., Sallinger, E.: Data wrangling for big data: towards a lingua franca for data wrangling. In: AMW (2016)

    Google Scholar 

  16. Gottlob, G., Orsi, G., Pieris, A.: Query rewriting and optimization for ontological databases. ACM Trans. Database Syst. 39(3), 25:1–25:46 (2014)

    Article  MathSciNet  Google Scholar 

  17. Gottlob, G., Pieris, A.: Beyond SPARQL under OWL 2 QL entailment regime: rules to the rescue. In: IJCAI, pp. 2999–3007 (2015)

    Google Scholar 

  18. Johnson, D.S., Klug, A.C.: Testing containment of conjunctive queries under functional and inclusion dependencies. J. Comput. Syst. Sci. 28(1), 167–189 (1984)

    Article  MathSciNet  Google Scholar 

  19. König, M., Leclère, M., Mugnier, M.-L., Thomazo, M.: Sound, complete and minimal ucq-rewriting for existential rules. Semant. Web 6(5), 451–475 (2015)

    Article  Google Scholar 

  20. Konstantinou, N., et al.: The VADA architecture for cost-effective data wrangling. In: SIGMOD, pp. 1599–1602 (2017)

    Google Scholar 

  21. Maier, D., Mendelzon, A.O., Sagiv, Y.: Testing implications of data dependencies. ACM Trans. Database Syst. 4(4), 455–469 (1979)

    Article  Google Scholar 

  22. Michels, C., Fayzrakhmanov, R.R., Ley, M., Sallinger, E., Schenkel, R.: OXpath-based data acquisition for DBLP. In: JCDL, pp. 319–320 (2017)

    Google Scholar 

  23. Shkapsky, A., Yang, M., Zaniolo, C.: Optimizing recursive queries with monotonic aggregates in deals. In: ICDE, pp. 867–878 (2015)

    Google Scholar 

Download references

Acknowledgements

This work has been supported by the EPSRC programme grant EP/M025268/1 VADA, the WWTF grant VRG18-013, the EU Horizon 2020 grant 809965, and the EPSRC grant EP/S003800/1 EQUID.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Georg Gottlob .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gottlob, G., Pieris, A., Sallinger, E. (2019). Vadalog: Recent Advances and Applications. In: Calimeri, F., Leone, N., Manna, M. (eds) Logics in Artificial Intelligence. JELIA 2019. Lecture Notes in Computer Science(), vol 11468. Springer, Cham. https://doi.org/10.1007/978-3-030-19570-0_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-19570-0_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19569-4

  • Online ISBN: 978-3-030-19570-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics