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FC-Datalog as a Framework for Efficient String Querying

Authors Owen M. Bell , Joel D. Day , Dominik D. Freydenberger

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ACM Subject Classification
  • Theory of computation → Logic and databases
Keywords
  • Information extraction
  • word equations
  • datalog
  • document spanners
  • regex

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Abstract

Core spanners are a class of document spanners that capture the core functionality of IBM’s AQL. FC is a logic on strings built around word equations that when extended with constraints for regular languages can be seen as a logic for core spanners. The recently introduced FC-Datalog extends FC with recursion, which allows us to define recursive relations for core spanners. Additionally, as FC-Datalog captures 𝖯, it is also a tractable version of Datalog on strings. This presents an opportunity for optimization.
We propose a series of FC-Datalog fragments with desirable properties in terms of complexity of model checking, expressive power, and efficiency of checking membership in the fragment. This leads to a range of fragments that all capture LOGSPACE, which we further restrict to obtain linear combined complexity. This gives us a framework to tailor fragments for particular applications. To showcase this, we simulate deterministic regex in a tailored fragment of FC-Datalog.

Cite As Get BibTex

Owen M. Bell, Joel D. Day, and Dominik D. Freydenberger. FC-Datalog as a Framework for Efficient String Querying. In 28th International Conference on Database Theory (ICDT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 328, pp. 29:1-29:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ICDT.2025.29

Author Details

Owen M. Bell
  • Loughborough University, UK
Joel D. Day
  • Loughborough University, UK
Dominik D. Freydenberger
  • Loughborough University, UK

Funding

This work was supported by EPSRC grant EP/T033762/1.

Acknowledgements

The authors would like to thank the anonymous reviewers of the current and previous versions for their detailed and helpful feedback.

Supplementary Materials

  • Data Accessibility: No data was generated or analyzed during this study.

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