2 Search Results for "Niehren, Joachim"


Document
Linear Programs with Conjunctive Queries

Authors: Florent Capelli, Nicolas Crosetti, Joachim Niehren, and Jan Ramon

Published in: LIPIcs, Volume 220, 25th International Conference on Database Theory (ICDT 2022)


Abstract
In this paper, we study the problem of optimizing a linear program whose variables are the answers to a conjunctive query. For this we propose the language LP(CQ) for specifying linear programs whose constraints and objective functions depend on the answer sets of conjunctive queries. We contribute an efficient algorithm for solving programs in a fragment of LP(CQ). The naive approach constructs a linear program having as many variables as there are elements in the answer set of the queries. Our approach constructs a linear program having the same optimal value but fewer variables. This is done by exploiting the structure of the conjunctive queries using generalized hypertree decompositions of small width to factorize elements of the answer set together. We illustrate the various applications of LP(CQ) programs on three examples: optimizing deliveries of resources, minimizing noise for differential privacy, and computing the s-measure of patterns in graphs as needed for data mining.

Cite as

Florent Capelli, Nicolas Crosetti, Joachim Niehren, and Jan Ramon. Linear Programs with Conjunctive Queries. In 25th International Conference on Database Theory (ICDT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 220, pp. 5:1-5:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{capelli_et_al:LIPIcs.ICDT.2022.5,
  author =	{Capelli, Florent and Crosetti, Nicolas and Niehren, Joachim and Ramon, Jan},
  title =	{{Linear Programs with Conjunctive Queries}},
  booktitle =	{25th International Conference on Database Theory (ICDT 2022)},
  pages =	{5:1--5:19},
  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 =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2022.5},
  URN =		{urn:nbn:de:0030-drops-158796},
  doi =		{10.4230/LIPIcs.ICDT.2022.5},
  annote =	{Keywords: Database queries, linear programming, hypergraph decomposition}
}
Document
N-ary Queries by Tree Automata

Authors: Joachim Niehren, Laurent Planque, Jean-Marc Talbot, and Sophie Tison

Published in: Dagstuhl Seminar Proceedings, Volume 5061, Foundations of Semistructured Data (2005)


Abstract
Information extraction from semi-structured documents requires to find n-ary queries in trees that define appropriate sets of n-tuples of nodes. We propose new representation formalisms for n-ary queries by tree automata that we prove to capture MSO. We then investigate n-ary queries by unambiguous tree automata which are relevant for query induction in multi-slot information extraction. We show that this representation formalism captures the class of n-ary queries that are finite unions of Cartesian closed queries, a property we prove decidable.

Cite as

Joachim Niehren, Laurent Planque, Jean-Marc Talbot, and Sophie Tison. N-ary Queries by Tree Automata. In Foundations of Semistructured Data. Dagstuhl Seminar Proceedings, Volume 5061, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)


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@InProceedings{niehren_et_al:DagSemProc.05061.5,
  author =	{Niehren, Joachim and Planque, Laurent and Talbot, Jean-Marc and Tison, Sophie},
  title =	{{N-ary Queries by Tree Automata}},
  booktitle =	{Foundations of Semistructured Data},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{5061},
  editor =	{Frank Neven and Thomas Schwentick and Dan Suciu},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.05061.5},
  URN =		{urn:nbn:de:0030-drops-2263},
  doi =		{10.4230/DagSemProc.05061.5},
  annote =	{Keywords: Information extraction, semistructured documents, node selecting queries in trees}
}
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