4 Search Results for "Livshits, Ester"

Document
DOI: 10.4230/LIPIcs.ICDT.2021.15
The Shapley Value of Inconsistency Measures for Functional Dependencies

Authors: Ester Livshits and Benny Kimelfeld

Published in: LIPIcs, Volume 186, 24th International Conference on Database Theory (ICDT 2021)

Abstract
Quantifying the inconsistency of a database is motivated by various goals including reliability estimation for new datasets and progress indication in data cleaning. Another goal is to attribute to individual tuples a level of responsibility to the overall inconsistency, and thereby prioritize tuples in the explanation or inspection of dirt. Therefore, inconsistency quantification and attribution have been a subject of much research in Knowledge Representation and, more recently, in Databases. As in many other fields, a conventional responsibility sharing mechanism is the Shapley value from cooperative game theory. In this paper, we carry out a systematic investigation of the complexity of the Shapley value in common inconsistency measures for functional-dependency (FD) violations. For several measures we establish a full classification of the FD sets into tractable and intractable classes with respect to Shapley-value computation. We also study the complexity of approximation in intractable cases.
Cite as

Ester Livshits and Benny Kimelfeld. The Shapley Value of Inconsistency Measures for Functional Dependencies. In 24th International Conference on Database Theory (ICDT 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 186, pp. 15:1-15:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{livshits_et_al:LIPIcs.ICDT.2021.15,
  author =	{Livshits, Ester and Kimelfeld, Benny},
  title =	{{The Shapley Value of Inconsistency Measures for Functional Dependencies}},
  booktitle =	{24th International Conference on Database Theory (ICDT 2021)},
  pages =	{15:1--15:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-179-5},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{186},
  editor =	{Yi, Ke and Wei, Zhewei},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2021.15},
  URN =		{urn:nbn:de:0030-drops-137230},
  doi =		{10.4230/LIPIcs.ICDT.2021.15},
  annote =	{Keywords: Shapley value, inconsistent databases, functional dependencies, database repairs}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2021.16
Database Repairing with Soft Functional Dependencies

Authors: Nofar Carmeli, Martin Grohe, Benny Kimelfeld, Ester Livshits, and Muhammad Tibi

Published in: LIPIcs, Volume 186, 24th International Conference on Database Theory (ICDT 2021)

Abstract
A common interpretation of soft constraints penalizes the database for every violation of every constraint, where the penalty is the cost (weight) of the constraint. A computational challenge is that of finding an optimal subset: a collection of database tuples that minimizes the total penalty when each tuple has a cost of being excluded. When the constraints are strict (i.e., have an infinite cost), this subset is a "cardinality repair" of an inconsistent database; in soft interpretations, this subset corresponds to a "most probable world" of a probabilistic database, a "most likely intention" of a probabilistic unclean database, and so on. Within the class of functional dependencies, the complexity of finding a cardinality repair is thoroughly understood. Yet, very little is known about the complexity of finding an optimal subset for the more general soft semantics. This paper makes a significant progress in this direction. In addition to general insights about the hardness and approximability of the problem, we present algorithms for two special cases: a single functional dependency, and a bipartite matching. The latter is the problem of finding an optimal "almost matching" of a bipartite graph where a penalty is paid for every lost edge and every violation of monogamy.
Cite as

Nofar Carmeli, Martin Grohe, Benny Kimelfeld, Ester Livshits, and Muhammad Tibi. Database Repairing with Soft Functional Dependencies. In 24th International Conference on Database Theory (ICDT 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 186, pp. 16:1-16:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{carmeli_et_al:LIPIcs.ICDT.2021.16,
  author =	{Carmeli, Nofar and Grohe, Martin and Kimelfeld, Benny and Livshits, Ester and Tibi, Muhammad},
  title =	{{Database Repairing with Soft Functional Dependencies}},
  booktitle =	{24th International Conference on Database Theory (ICDT 2021)},
  pages =	{16:1--16:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-179-5},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{186},
  editor =	{Yi, Ke and Wei, Zhewei},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2021.16},
  URN =		{urn:nbn:de:0030-drops-137245},
  doi =		{10.4230/LIPIcs.ICDT.2021.16},
  annote =	{Keywords: Database inconsistency, database repairs, integrity constraints, soft constraints, functional dependencies}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2020.20
The Shapley Value of Tuples in Query Answering

Authors: Ester Livshits, Leopoldo Bertossi, Benny Kimelfeld, and Moshe Sebag

Published in: LIPIcs, Volume 155, 23rd International Conference on Database Theory (ICDT 2020)

Abstract
We investigate the application of the Shapley value to quantifying the contribution of a tuple to a query answer. The Shapley value is a widely known numerical measure in cooperative game theory and in many applications of game theory for assessing the contribution of a player to a coalition game. It has been established already in the 1950s, and is theoretically justified by being the very single wealth-distribution measure that satisfies some natural axioms. While this value has been investigated in several areas, it received little attention in data management. We study this measure in the context of conjunctive and aggregate queries by defining corresponding coalition games. We provide algorithmic and complexity-theoretic results on the computation of Shapley-based contributions to query answers; and for the hard cases we present approximation algorithms.
Cite as

Ester Livshits, Leopoldo Bertossi, Benny Kimelfeld, and Moshe Sebag. The Shapley Value of Tuples in Query Answering. In 23rd International Conference on Database Theory (ICDT 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 155, pp. 20:1-20:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{livshits_et_al:LIPIcs.ICDT.2020.20,
  author =	{Livshits, Ester and Bertossi, Leopoldo and Kimelfeld, Benny and Sebag, Moshe},
  title =	{{The Shapley Value of Tuples in Query Answering}},
  booktitle =	{23rd International Conference on Database Theory (ICDT 2020)},
  pages =	{20:1--20:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-139-9},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{155},
  editor =	{Lutz, Carsten and Jung, Jean Christoph},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2020.20},
  URN =		{urn:nbn:de:0030-drops-119442},
  doi =		{10.4230/LIPIcs.ICDT.2020.20},
  annote =	{Keywords: Shapley value, query answering, conjunctive queries, aggregate queries}
}
Document
DOI: 10.4230/LIPIcs.ICDT.2017.17
Detecting Ambiguity in Prioritized Database Repairing

Authors: Benny Kimelfeld, Ester Livshits, and Liat Peterfreund

Published in: LIPIcs, Volume 68, 20th International Conference on Database Theory (ICDT 2017)

Abstract
In its traditional definition, a repair of an inconsistent database is a consistent database that differs from the inconsistent one in a "minimal way." Often, repairs are not equally legitimate, as it is desired to prefer one over another; for example, one fact is regarded more reliable than another, or a more recent fact should be preferred to an earlier one. Motivated by these considerations, researchers have introduced and investigated the framework of preferred repairs, in the context of denial constraints and subset repairs. There, a priority relation between facts is lifted towards a priority relation between consistent databases, and repairs are restricted to the ones that are optimal in the lifted sense. Three notions of lifting (and optimal repairs) have been proposed: Pareto, global, and completion. In this paper we investigate the complexity of deciding whether the priority relation suffices to clean the database unambiguously, or in other words, whether there is exactly one optimal repair. We show that the different lifting semantics entail highly different complexities. Under Pareto optimality, the problem is coNP-complete, in data complexity, for every set of functional dependencies (FDs), except for the tractable case of (equivalence to) one FD per relation. Under global optimality, one FD per relation is still tractable, but we establish Pi-2-p-completeness for a relation with two FDs. In contrast, under completion optimality the problem is solvable in polynomial time for every set of FDs. In fact, we present a polynomial-time algorithm for arbitrary conflict hypergraphs. We further show that under a general assumption of transitivity, this algorithm solves the problem even for global optimality. The algorithm is extremely simple, but its proof of correctness is quite intricate.
Cite as

Benny Kimelfeld, Ester Livshits, and Liat Peterfreund. Detecting Ambiguity in Prioritized Database Repairing. In 20th International Conference on Database Theory (ICDT 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 68, pp. 17:1-17:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

Copy BibTex To Clipboard

@InProceedings{kimelfeld_et_al:LIPIcs.ICDT.2017.17,
  author =	{Kimelfeld, Benny and Livshits, Ester and Peterfreund, Liat},
  title =	{{Detecting Ambiguity in Prioritized Database Repairing}},
  booktitle =	{20th International Conference on Database Theory (ICDT 2017)},
  pages =	{17:1--17:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-024-8},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{68},
  editor =	{Benedikt, Michael and Orsi, Giorgio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2017.17},
  URN =		{urn:nbn:de:0030-drops-70489},
  doi =		{10.4230/LIPIcs.ICDT.2017.17},
  annote =	{Keywords: inconsistent databases, preferred repairs, data cleaning, functional dependencies, conflict hypergraph}
}
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