Causes for query answers from databases: Datalog abduction, view-updates, and integrity constraints

Bertossi, Leopoldo; Salimi, Babak

doi:10.1016/j.ijar.2017.07.010

Cited by 27 publications

(35 citation statements)

References 58 publications

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“…These notions can be applied to any monotonic query (i.e., whose answer set can only grow when the database grows, e.g., UCQs and Datalog queries)[BS17b,BS17a].…”

mentioning

confidence: 99%

The Shapley Value of Tuples in Query Answering

Livshits¹,

Bertossi²,

Kimelfeld³

et al. 2021

Logical Methods in Computer Science

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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.

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“…These notions can be applied to any monotonic query (i.e., whose answer set can only grow when the database grows, e.g., UCQs and Datalog queries)[BS17b,BS17a].…”

mentioning

confidence: 99%

The Shapley Value of Tuples in Query Answering

Livshits¹,

Bertossi²,

Kimelfeld³

et al. 2021

Logical Methods in Computer Science

Self Cite

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“…It is also similar to being a relevant hypothesis in the context of abductive diagnosis [6,10,11]. We refer the reader to Bertossi and Salimi [4] who have established the connection between causal responsibility and abductive diagnosis.…”

Section: Introductionmentioning

confidence: 61%

“…It is straightforward to show that the relevance to a CQ without negation can be decided in polynomial time. The problem is known to be NP-complete for Datalog programs with recursion [4]. We now show that there exists a CQ ¬ q containing a polarityconsistent relation T , such that the relevance of a T -fact to q is NP-complete.…”

Section: Hardness Of Multiplicative Approximationmentioning

confidence: 86%

“…In the contrapositive, if we prove that the relevance to the query is an intractable decision problem, then we also establish the intractability of an FPRAS approximation. Yet, the relevance is tractable for positive CQs, and hardness results are known only for Datalog programs with recursion [4,11]. We prove here the existence of a CQ and a polarity-consistent fact f such that the decision of relevance to the query (and, hence, the multiplicative approximation of the Shapley value) is intractable.…”

Section: Introductionmentioning

confidence: 93%

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The Impact of Negation on the Complexity of the Shapley Value in Conjunctive Queries

Reshef¹,

Kimelfeld²,

Livshits³

2019

Preprint

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The Shapley value is a conventional and well-studied function for determining the contribution of a player to the coalition in a cooperative game. Among its applications in a plethora of domains, it has recently been proposed to use the Shapley value for quantifying the contribution of a tuple to the result of a database query.In particular, we have a thorough understanding of the tractability frontier for the class of Conjunctive Queries (CQs) and aggregate functions over CQs. It has also been established that a tractable (randomized) multiplicative approximation exists for every union of CQs. Nevertheless, all of these results are based on the monotonicity of CQs. In this work, we investigate the implication of negation on the complexity of Shapley computation, in both the exact and approximate senses. We generalize a known dichotomy to account for negated atoms. We also show that negation fundamentally changes the complexity of approximation. We do so by drawing a connection to the problem of deciding whether a tuple is "relevant" to a query, and by analyzing its complexity.

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“…Computing causes for CQs can be done in polynomial time in data [33], which also holds for UBCQs [9]. In [10] it was established that cause computation for Datalog queries falls in the second level of the polynomial hierarchy (PH). As has been established in [33,9], the computational problems associated to contingency sets and responsibility are at the second level of PH, in data complexity.…”

Section: Discussionmentioning

confidence: 99%

Characterizing and Computing Causes for Query Answers in Databases from Database Repairs and Repair Programs

Bertossi

2018

Lecture Notes in Computer Science

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A correspondence between database tuples as causes for query answers in databases and tuple-based repairs of inconsistent databases with respect to denial constraints has already been established. In this work, answerset programs that specify repairs of databases are used as a basis for solving computational and reasoning problems about causes. Here, causes are also introduced at the attribute level by appealing to a both null-based and attributebased repair semantics. The corresponding repair programs are presented, and they are used as a basis for computation and reasoning about attribute-level causes. They are extended to deal with the case of causality under integrity constraints. Several examples with the DLV system are shown.

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Causes for query answers from databases: Datalog abduction, view-updates, and integrity constraints

Cited by 27 publications

References 58 publications

The Shapley Value of Tuples in Query Answering

The Shapley Value of Tuples in Query Answering

The Impact of Negation on the Complexity of the Shapley Value in Conjunctive Queries

Characterizing and Computing Causes for Query Answers in Databases from Database Repairs and Repair Programs

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