License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ICDT.2022.14
URN: urn:nbn:de:0030-drops-158889
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Groz, Benoît ; Lemay, Aurélien ; Staworko, Sławek ; Wieczorek, Piotr

Inference of Shape Graphs for Graph Databases

LIPIcs-ICDT-2022-14.pdf (0.9 MB)


We investigate the problem of constructing a shape graph that describes the structure of a given graph database. We employ the framework of grammatical inference, where the objective is to find an inference algorithm that is both sound, i.e., always producing a schema that validates the input graph, and complete, i.e., able to produce any schema, within a given class of schemas, provided that a sufficiently informative input graph is presented. We identify a number of fundamental limitations that preclude feasible inference. We present inference algorithms based on natural approaches that allow to infer schemas that we argue to be of practical importance.

BibTeX - Entry

  author =	{Groz, Beno\^{i}t and Lemay, Aur\'{e}lien and Staworko, S{\l}awek and Wieczorek, Piotr},
  title =	{{Inference of Shape Graphs for Graph Databases}},
  booktitle =	{25th International Conference on Database Theory (ICDT 2022)},
  pages =	{14:1--14:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-223-5},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{220},
  editor =	{Olteanu, Dan and Vortmeier, Nils},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-158889},
  doi =		{10.4230/LIPIcs.ICDT.2022.14},
  annote =	{Keywords: RDF, Schema, Inference, Learning, Fitting, Minimality, Containment}

Keywords: RDF, Schema, Inference, Learning, Fitting, Minimality, Containment
Collection: 25th International Conference on Database Theory (ICDT 2022)
Issue Date: 2022
Date of publication: 19.03.2022

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