3 Search Results for "Beierle, Christoph"


Document
Enumeration of Minimal Hitting Sets Parameterized by Treewidth

Authors: Batya Kenig and Dan Shlomo Mizrahi

Published in: LIPIcs, Volume 328, 28th International Conference on Database Theory (ICDT 2025)


Abstract
Enumerating the minimal hitting sets of a hypergraph is a problem which arises in many data management applications that include constraint mining, discovering unique column combinations, and enumerating database repairs. Previously, Eiter et al. [Thomas Eiter et al., 2003] showed that the minimal hitting sets of an n-vertex hypergraph, with treewidth w, can be enumerated with delay O^*(n^w) (ignoring polynomial factors), with space requirements that scale with the output size. We improve this to fixed-parameter-linear delay, following an FPT preprocessing phase. The memory consumption of our algorithm is exponential with respect to the treewidth of the hypergraph.

Cite as

Batya Kenig and Dan Shlomo Mizrahi. Enumeration of Minimal Hitting Sets Parameterized by Treewidth. In 28th International Conference on Database Theory (ICDT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 328, pp. 8:1-8:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{kenig_et_al:LIPIcs.ICDT.2025.8,
  author =	{Kenig, Batya and Mizrahi, Dan Shlomo},
  title =	{{Enumeration of Minimal Hitting Sets Parameterized by Treewidth}},
  booktitle =	{28th International Conference on Database Theory (ICDT 2025)},
  pages =	{8:1--8:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-364-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{328},
  editor =	{Roy, Sudeepa and Kara, Ahmet},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2025.8},
  URN =		{urn:nbn:de:0030-drops-229498},
  doi =		{10.4230/LIPIcs.ICDT.2025.8},
  annote =	{Keywords: Enumeration, Hitting sets}
}
Document
Position
Grounding Stream Reasoning Research

Authors: Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1


Abstract
In the last decade, there has been a growing interest in applying AI technologies to implement complex data analytics over data streams. To this end, researchers in various fields have been organising a yearly event called the "Stream Reasoning Workshop" to share perspectives, challenges, and experiences around this topic. In this paper, the previous organisers of the workshops and other community members provide a summary of the main research results that have been discussed during the first six editions of the event. These results can be categorised into four main research areas: The first is concerned with the technological challenges related to handling large data streams. The second area aims at adapting and extending existing semantic technologies to data streams. The third and fourth areas focus on how to implement reasoning techniques, either considering deductive or inductive techniques, to extract new and valuable knowledge from the data in the stream. This summary is written not only to provide a crystallisation of the field, but also to point out distinctive traits of the stream reasoning community. Moreover, it also provides a foundation for future research by enumerating a list of use cases and open challenges, to stimulate others to join this exciting research area.

Cite as

Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer. Grounding Stream Reasoning Research. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 2:1-2:47, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@Article{bonte_et_al:TGDK.2.1.2,
  author =	{Bonte, Pieter and Calbimonte, Jean-Paul and de Leng, Daniel and Dell'Aglio, Daniele and Della Valle, Emanuele and Eiter, Thomas and Giannini, Federico and Heintz, Fredrik and Schekotihin, Konstantin and Le-Phuoc, Danh and Mileo, Alessandra and Schneider, Patrik and Tommasini, Riccardo and Urbani, Jacopo and Ziffer, Giacomo},
  title =	{{Grounding Stream Reasoning Research}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:47},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.2},
  URN =		{urn:nbn:de:0030-drops-198597},
  doi =		{10.4230/TGDK.2.1.2},
  annote =	{Keywords: Stream Reasoning, Stream Processing, RDF streams, Streaming Linked Data, Continuous query processing, Temporal Logics, High-performance computing, Databases}
}
Document
Modelling and Implementing a Knowledge Base for Checking Medical Invoices with DLV

Authors: Gabriele Kern-Isberner, Christoph Beierle, and Oliver Dusso

Published in: Dagstuhl Seminar Proceedings, Volume 5171, Nonmonotonic Reasoning, Answer Set Programming and Constraints (2005)


Abstract
Checking medical invoices, done by every health insurance company, is a labor-intensive task. Both speed and quality of executing this task may be increased by the knowledge-based decision support system ACMI which we present in this paper. As the relevant regulations also contain various default rules, ACMI`s knowledge core is modelled using the answer set programming paradigm. It turned out that all relevant rules could be expressed directly in this framework, providing for a declarative and easily extendable and modifiable knowledge base. ACMI is implemented using the DLV system.

Cite as

Gabriele Kern-Isberner, Christoph Beierle, and Oliver Dusso. Modelling and Implementing a Knowledge Base for Checking Medical Invoices with DLV. In Nonmonotonic Reasoning, Answer Set Programming and Constraints. Dagstuhl Seminar Proceedings, Volume 5171, pp. 1-12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)


Copy BibTex To Clipboard

@InProceedings{kernisberner_et_al:DagSemProc.05171.4,
  author =	{Kern-Isberner, Gabriele and Beierle, Christoph and Dusso, Oliver},
  title =	{{Modelling and Implementing a Knowledge Base for Checking Medical Invoices with DLV}},
  booktitle =	{Nonmonotonic Reasoning, Answer Set Programming and Constraints},
  pages =	{1--12},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{5171},
  editor =	{Gerhard Brewka and Ilkka Niemel\"{a} and Torsten Schaub and Miroslaw Truszczynski},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05171.4},
  URN =		{urn:nbn:de:0030-drops-2610},
  doi =		{10.4230/DagSemProc.05171.4},
  annote =	{Keywords: Answer sets, default rules, health insurance, rule schemas}
}
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