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Documents authored by Olteanu, Dan

Document
DOI: 10.4230/LIPIcs.ICDT.2023.17
Conjunctive Queries with Free Access Patterns Under Updates

Authors: Ahmet Kara, Milos Nikolic, Dan Olteanu, and Haozhe Zhang

Published in: LIPIcs, Volume 255, 26th International Conference on Database Theory (ICDT 2023)

Abstract
We study the problem of answering conjunctive queries with free access patterns under updates. A free access pattern is a partition of the free variables of the query into input and output. The query returns tuples over the output variables given a tuple of values over the input variables. We introduce a fully dynamic evaluation approach for such queries. We also give a syntactic characterisation of those queries that admit constant time per single-tuple update and whose output tuples can be enumerated with constant delay given an input tuple. Finally, we chart the complexity trade-off between the preprocessing time, update time and enumeration delay for such queries. For a class of queries, our approach achieves optimal, albeit non-constant, update time and delay. Their optimality is predicated on the Online Matrix-Vector Multiplication conjecture. Our results recover prior work on the dynamic evaluation of conjunctive queries without access patterns.
Cite as

Ahmet Kara, Milos Nikolic, Dan Olteanu, and Haozhe Zhang. Conjunctive Queries with Free Access Patterns Under Updates. In 26th International Conference on Database Theory (ICDT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 255, pp. 17:1-17:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{kara_et_al:LIPIcs.ICDT.2023.17,
  author =	{Kara, Ahmet and Nikolic, Milos and Olteanu, Dan and Zhang, Haozhe},
  title =	{{Conjunctive Queries with Free Access Patterns Under Updates}},
  booktitle =	{26th International Conference on Database Theory (ICDT 2023)},
  pages =	{17:1--17:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-270-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{255},
  editor =	{Geerts, Floris and Vandevoort, Brecht},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2023.17},
  URN =		{urn:nbn:de:0030-drops-177599},
  doi =		{10.4230/LIPIcs.ICDT.2023.17},
  annote =	{Keywords: fully dynamic algorithm, enumeration delay, complexity trade-off, dichotomy}
}
Document
DOI: 10.4230/LIPIcs.CSL.2023.29
Evaluation Trade-Offs for Acyclic Conjunctive Queries

Authors: Ahmet Kara, Milos Nikolic, Dan Olteanu, and Haozhe Zhang

Published in: LIPIcs, Volume 252, 31st EACSL Annual Conference on Computer Science Logic (CSL 2023)

Abstract
We consider the evaluation of acyclic conjunctive queries, where the evaluation time is decomposed into preprocessing time and enumeration delay. In a seminal paper at CSL'07, Bagan, Durand, and Grandjean showed that acyclic queries can be evaluated with linear preprocessing time and linear enumeration delay. If the query is free-connex, the enumeration delay becomes constant. Further prior work showed that constant enumeration delay can be achieved for arbitrary acyclic conjunctive queries at the expense of a preprocessing time that is characterised by the fractional hypertree width. We introduce an approach that exposes a trade-off between preprocessing time and enumeration delay for acyclic conjunctive queries. The aforementioned prior works represent extremes in this trade-off space. Yet our approach also allows for the enumeration delay and the preprocessing time between these extremes, in particular the delay may lie between constant and linear time. Our approach decomposes the given query into subqueries and achieves for each subquery a trade-off that depends on a parameter controlling the times for preprocessing and enumeration. The complexity of the query is given by the Pareto optimal points of a bi-objective optimisation program whose inputs are possible query decompositions and parameter values.
Cite as

Ahmet Kara, Milos Nikolic, Dan Olteanu, and Haozhe Zhang. Evaluation Trade-Offs for Acyclic Conjunctive Queries. In 31st EACSL Annual Conference on Computer Science Logic (CSL 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 252, pp. 29:1-29:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{kara_et_al:LIPIcs.CSL.2023.29,
  author =	{Kara, Ahmet and Nikolic, Milos and Olteanu, Dan and Zhang, Haozhe},
  title =	{{Evaluation Trade-Offs for Acyclic Conjunctive Queries}},
  booktitle =	{31st EACSL Annual Conference on Computer Science Logic (CSL 2023)},
  pages =	{29:1--29:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-264-8},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{252},
  editor =	{Klin, Bartek and Pimentel, Elaine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2023.29},
  URN =		{urn:nbn:de:0030-drops-174907},
  doi =		{10.4230/LIPIcs.CSL.2023.29},
  annote =	{Keywords: acyclic queries, query evaluation, enumeration delay}
}
Document
Complete Volume
DOI: 10.4230/LIPIcs.ICDT.2022
LIPIcs, Volume 220, ICDT 2022, Complete Volume

Authors: Dan Olteanu and Nils Vortmeier

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

Abstract
LIPIcs, Volume 220, ICDT 2022, Complete Volume
Cite as

25th International Conference on Database Theory (ICDT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 220, pp. 1-354, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@Proceedings{olteanu_et_al:LIPIcs.ICDT.2022,
  title =	{{LIPIcs, Volume 220, ICDT 2022, Complete Volume}},
  booktitle =	{25th International Conference on Database Theory (ICDT 2022)},
  pages =	{1--354},
  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},
  URN =		{urn:nbn:de:0030-drops-158737},
  doi =		{10.4230/LIPIcs.ICDT.2022},
  annote =	{Keywords: LIPIcs, Volume 220, ICDT 2022, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/LIPIcs.ICDT.2022.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Dan Olteanu and Nils Vortmeier

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

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

25th International Conference on Database Theory (ICDT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 220, pp. 0:i-0:xvi, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{olteanu_et_al:LIPIcs.ICDT.2022.0,
  author =	{Olteanu, Dan and Vortmeier, Nils},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{25th International Conference on Database Theory (ICDT 2022)},
  pages =	{0:i--0:xvi},
  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.2022.0},
  URN =		{urn:nbn:de:0030-drops-158745},
  doi =		{10.4230/LIPIcs.ICDT.2022.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.ICDT.2019.1
Learning Models over Relational Databases (Invited Talk)

Authors: Dan Olteanu

Published in: LIPIcs, Volume 127, 22nd International Conference on Database Theory (ICDT 2019)

Abstract
In this talk, I will make the case for a first-principles approach to machine learning over relational databases that exploits recent development in database systems and theory. The input to learning classification and regression models is defined by feature extraction queries over relational databases. The mainstream approach to learning over relational data is to materialize the training dataset, export it out of the database, and then learn over it using statistical software packages. These three steps are expensive and unnecessary. Instead, one can cast the machine learning problem as a database problem by decomposing the learning task into a batch of aggregates over the feature extraction query and by computing this batch over the input database. The performance of this database-centric approach benefits tremendously from structural properties of the relational data and of the feature extraction query; such properties may be algebraic (semi-ring), combinatorial (hypertree width), or statistical (sampling). It also benefits from database systems techniques such as factorized query evaluation and query compilation. For a variety of models, including factorization machines, decision trees, and support vector machines, this approach may come with lower computational complexity than the materialization of the training dataset used by the mainstream approach. Recent results show that this translates to several orders-of-magnitude speed-up over state-of-the-art systems such as TensorFlow, R, Scikit-learn, and mlpack. While these initial results are promising, there is much more awaiting to be discovered.
Cite as

Dan Olteanu. Learning Models over Relational Databases (Invited Talk). In 22nd International Conference on Database Theory (ICDT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 127, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{olteanu:LIPIcs.ICDT.2019.1,
  author =	{Olteanu, Dan},
  title =	{{Learning Models over Relational Databases}},
  booktitle =	{22nd International Conference on Database Theory (ICDT 2019)},
  pages =	{1:1--1:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-101-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{127},
  editor =	{Barcelo, Pablo and Calautti, Marco},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2019.1},
  URN =		{urn:nbn:de:0030-drops-103034},
  doi =		{10.4230/LIPIcs.ICDT.2019.1},
  annote =	{Keywords: In-database analytics, Data complexity, Feature extraction queries, Database dependencies, Model reparameterization}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2019.4
Counting Triangles under Updates in Worst-Case Optimal Time

Authors: Ahmet Kara, Hung Q. Ngo, Milos Nikolic, Dan Olteanu, and Haozhe Zhang

Published in: LIPIcs, Volume 127, 22nd International Conference on Database Theory (ICDT 2019)

Abstract
We consider the problem of incrementally maintaining the triangle count query under single-tuple updates to the input relations. We introduce an approach that exhibits a space-time tradeoff such that the space-time product is quadratic in the size of the input database and the update time can be as low as the square root of this size. This lowest update time is worst-case optimal conditioned on the Online Matrix-Vector Multiplication conjecture. The classical and factorized incremental view maintenance approaches are recovered as special cases of our approach within the space-time tradeoff. In particular, they require linear-time maintenance under updates, which is suboptimal. Our approach can also count all triangles in a static database in the worst-case optimal time needed for enumerating them.
Cite as

Ahmet Kara, Hung Q. Ngo, Milos Nikolic, Dan Olteanu, and Haozhe Zhang. Counting Triangles under Updates in Worst-Case Optimal Time. In 22nd International Conference on Database Theory (ICDT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 127, pp. 4:1-4:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{kara_et_al:LIPIcs.ICDT.2019.4,
  author =	{Kara, Ahmet and Ngo, Hung Q. and Nikolic, Milos and Olteanu, Dan and Zhang, Haozhe},
  title =	{{Counting Triangles under Updates in Worst-Case Optimal Time}},
  booktitle =	{22nd International Conference on Database Theory (ICDT 2019)},
  pages =	{4:1--4:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-101-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{127},
  editor =	{Barcelo, Pablo and Calautti, Marco},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2019.4},
  URN =		{urn:nbn:de:0030-drops-103068},
  doi =		{10.4230/LIPIcs.ICDT.2019.4},
  annote =	{Keywords: incremental view maintenance, amortized analysis, data skew}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2019.21
Boolean Tensor Decomposition for Conjunctive Queries with Negation

Authors: Mahmoud Abo Khamis, Hung Q. Ngo, Dan Olteanu, and Dan Suciu

Published in: LIPIcs, Volume 127, 22nd International Conference on Database Theory (ICDT 2019)

Abstract
We propose an approach for answering conjunctive queries with negation, where the negated relations have bounded degree. Its data complexity matches that of the InsideOut and PANDA algorithms for the positive subquery of the input query and is expressed in terms of the fractional hypertree width and the submodular width respectively. Its query complexity depends on the structure of the conjunction of negated relations; in general it is exponential in the number of join variables occurring in negated relations yet it becomes polynomial for several classes of queries. This approach relies on several contributions. We show how to rewrite queries with negation on bounded-degree relations into equivalent conjunctive queries with not-all-equal (NAE) predicates, which are a multi-dimensional analog of disequality (!=). We then generalize the known color-coding technique to conjunctions of NAE predicates and explain it via a Boolean tensor decomposition of conjunctions of NAE predicates. This decomposition can be achieved via a probabilistic construction that can be derandomized efficiently.
Cite as

Mahmoud Abo Khamis, Hung Q. Ngo, Dan Olteanu, and Dan Suciu. Boolean Tensor Decomposition for Conjunctive Queries with Negation. In 22nd International Conference on Database Theory (ICDT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 127, pp. 21:1-21:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{abokhamis_et_al:LIPIcs.ICDT.2019.21,
  author =	{Abo Khamis, Mahmoud and Ngo, Hung Q. and Olteanu, Dan and Suciu, Dan},
  title =	{{Boolean Tensor Decomposition for Conjunctive Queries with Negation}},
  booktitle =	{22nd International Conference on Database Theory (ICDT 2019)},
  pages =	{21:1--21:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-101-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{127},
  editor =	{Barcelo, Pablo and Calautti, Marco},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2019.21},
  URN =		{urn:nbn:de:0030-drops-103236},
  doi =		{10.4230/LIPIcs.ICDT.2019.21},
  annote =	{Keywords: color-coding, combined complexity, negation, query evaluation}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2018.16
Covers of Query Results

Authors: Ahmet Kara and Dan Olteanu

Published in: LIPIcs, Volume 98, 21st International Conference on Database Theory (ICDT 2018)

Abstract
We introduce succinct lossless representations of query results called covers. They are subsets of the query results that correspond to minimal edge covers in the hypergraphs of these results. We first study covers whose structures are given by fractional hypertree decompositions of join queries. For any decomposition of a query, we give asymptotically tight size bounds for the covers of the query result over that decomposition and show that such covers can be computed in worst-case optimal time up to a logarithmic factor in the database size. For acyclic join queries, we can compute covers compositionally using query plans with a new operator called cover-join. The tuples in the query result can be enumerated from any of its covers with linearithmic pre-computation time and constant delay. We then generalize covers from joins to functional aggregate queries that express a host of computational problems such as aggregate-join queries, in-database optimization, matrix chain multiplication, and inference in probabilistic graphical models.
Cite as

Ahmet Kara and Dan Olteanu. Covers of Query Results. In 21st International Conference on Database Theory (ICDT 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 98, pp. 16:1-16:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{kara_et_al:LIPIcs.ICDT.2018.16,
  author =	{Kara, Ahmet and Olteanu, Dan},
  title =	{{Covers of Query Results}},
  booktitle =	{21st International Conference on Database Theory (ICDT 2018)},
  pages =	{16:1--16:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-063-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{98},
  editor =	{Kimelfeld, Benny and Amsterdamer, Yael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2018.16},
  URN =		{urn:nbn:de:0030-drops-86100},
  doi =		{10.4230/LIPIcs.ICDT.2018.16},
  annote =	{Keywords: factorized database, fractional hypertree decomposition, functional aggregate query, minimal edge cover, query plan}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2016.7
Declarative Probabilistic Programming with Datalog

Authors: Vince Barany, Balder ten Cate, Benny Kimelfeld, Dan Olteanu, and Zografoula Vagena

Published in: LIPIcs, Volume 48, 19th International Conference on Database Theory (ICDT 2016)

Abstract
Probabilistic programming languages are used for developing statistical models, and they typically consist of two components: a specification of a stochastic process (the prior), and a specification of observations that restrict the probability space to a conditional subspace (the posterior). Use cases of such formalisms include the development of algorithms in machine learning and artificial intelligence. We propose and investigate an extension of Datalog for specifying statistical models, and establish a declarative probabilistic-programming paradigm over databases. Our proposed extension provides convenient mechanisms to include common numerical probability functions; in particular, conclusions of rules may contain values drawn from such functions. The semantics of a program is a probability distribution over the possible outcomes of the input database with respect to the program. Observations are naturally incorporated by means of integrity constraints over the extensional and intensional relations. The resulting semantics is robust under different chases and invariant to rewritings that preserve logical equivalence.
Cite as

Vince Barany, Balder ten Cate, Benny Kimelfeld, Dan Olteanu, and Zografoula Vagena. Declarative Probabilistic Programming with Datalog. In 19th International Conference on Database Theory (ICDT 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 48, pp. 7:1-7:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{barany_et_al:LIPIcs.ICDT.2016.7,
  author =	{Barany, Vince and ten Cate, Balder and Kimelfeld, Benny and Olteanu, Dan and Vagena, Zografoula},
  title =	{{Declarative Probabilistic Programming with Datalog}},
  booktitle =	{19th International Conference on Database Theory (ICDT 2016)},
  pages =	{7:1--7:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-002-6},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{48},
  editor =	{Martens, Wim and Zeume, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2016.7},
  URN =		{urn:nbn:de:0030-drops-57761},
  doi =		{10.4230/LIPIcs.ICDT.2016.7},
  annote =	{Keywords: Chase, Datalog, probability measure space, probabilistic programming}
}
Document
DOI: 10.4230/DagSemProc.08421.3
08421 Working Group: Classification, Representation and Modeling

Authors: Anish Das Sarma, Ander de Keijzer, Amol Deshpande, Peter J. Haas, Ihab F. Ilyas, Christoph Koch, Thomas Neumann, Dan Olteanu, Martin Theobald, and Vasilis Vassalos

Published in: Dagstuhl Seminar Proceedings, Volume 8421, Uncertainty Management in Information Systems (2009)

Abstract
This report briefly summarizes the discussions carried out in the working group on classification, representation and modeling of uncertain data. The discussion was divided into two subgroups: the first subgroup studied how different representation and modeling alternatives currently proposed can fit in a bigger picture of theory and technology interaction, while the second subgroup focused on contrasting current system implementations and the reasons behind such diverse class of available prototypes. We summarize the findings of these two groups and the future steps suggested by group members.
Cite as

Anish Das Sarma, Ander de Keijzer, Amol Deshpande, Peter J. Haas, Ihab F. Ilyas, Christoph Koch, Thomas Neumann, Dan Olteanu, Martin Theobald, and Vasilis Vassalos. 08421 Working Group: Classification, Representation and Modeling. In Uncertainty Management in Information Systems. Dagstuhl Seminar Proceedings, Volume 8421, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{dassarma_et_al:DagSemProc.08421.3,
  author =	{Das Sarma, Anish and de Keijzer, Ander and Deshpande, Amol and Haas, Peter J. and Ilyas, Ihab F. and Koch, Christoph and Neumann, Thomas and Olteanu, Dan and Theobald, Martin and Vassalos, Vasilis},
  title =	{{08421 Working Group: Classification, Representation and Modeling}},
  booktitle =	{Uncertainty Management in Information Systems},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{8421},
  editor =	{Christoph Koch and Birgitta K\"{o}nig-Ries and Volker Markl and Maurice van Keulen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.08421.3},
  URN =		{urn:nbn:de:0030-drops-19410},
  doi =		{10.4230/DagSemProc.08421.3},
  annote =	{Keywords: }
}
Document
DOI: 10.4230/DagSemProc.08421.7
08421 Working Group: Report of the Probabilistic Databases Benchmarking

Authors: Christoph Koch, Peter J. Haas, H.-J. Lenz, Dan Olteanu, Christopher Re, Maurice van Keulen, and Jeff Z. Pan

Published in: Dagstuhl Seminar Proceedings, Volume 8421, Uncertainty Management in Information Systems (2009)

Abstract
The results of the probabilistic database benchmark working group.
Cite as

Christoph Koch, Peter J. Haas, H.-J. Lenz, Dan Olteanu, Christopher Re, Maurice van Keulen, and Jeff Z. Pan. 08421 Working Group: Report of the Probabilistic Databases Benchmarking. In Uncertainty Management in Information Systems. Dagstuhl Seminar Proceedings, Volume 8421, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{koch_et_al:DagSemProc.08421.7,
  author =	{Koch, Christoph and Haas, Peter J. and Lenz, H.-J. and Olteanu, Dan and Re, Christopher and van Keulen, Maurice and Pan, Jeff Z.},
  title =	{{08421 Working Group: Report of the Probabilistic Databases Benchmarking}},
  booktitle =	{Uncertainty Management in Information Systems},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{8421},
  editor =	{Christoph Koch and Birgitta K\"{o}nig-Ries and Volker Markl and Maurice van Keulen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.08421.7},
  URN =		{urn:nbn:de:0030-drops-19367},
  doi =		{10.4230/DagSemProc.08421.7},
  annote =	{Keywords: Probabilistic databases, benchmark}
}
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