The complexity of relational query languages (Extended Abstract)

Vardi, Moshe Y.

doi:10.1145/800070.802186

Cited by 1,019 publications

(675 citation statements)

References 18 publications

(4 reference statements)

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“…This work has shown that most of the languages proposed so far are not really suited for this task. Indeed, the most significant fragments of OWL [14] 3 that have been proposed by the W3C (namely, OWL-DL and OWL-Lite) are actually coNP-hard in data complexity [10,7], i.e., when complexity is measured with respect to the size of the data layer only, which is indeed the dominant parameter in this context [31]. This means that, in practice, computations over large amounts of data are prohibitively costly.…”

Section: Introductionmentioning

confidence: 99%

Linking Data to Ontologies

Poggi

Lembo

Calvanese

et al. 2008

Lecture Notes in Computer Science

503

523

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Abstract. Many organizations nowadays face the problem of accessing existing data sources by means of flexible mechanisms that are both powerful and efficient. Ontologies are widely considered as a suitable formal tool for sophisticated data access. The ontology expresses the domain of interest of the information system at a high level of abstraction, and the relationship between data at the sources and instances of concepts and roles in the ontology is expressed by means of mappings. In this paper we present a solution to the problem of designing effective systems for ontology-based data access. Our solution is based on three main ingredients. First, we present a new ontology language, based on Description Logics, that is particularly suited to reason with large amounts of instances. The second ingredient is a novel mapping language that is able to deal with the so-called impedance mismatch problem, i.e., the problem arising from the difference between the basic elements managed by the sources, namely data, and the elements managed by the ontology, namely objects. The third ingredient is the query answering method, that combines reasoning at the level of the ontology with specific mechanisms for both taking into account the mappings and efficiently accessing the data at the sources.

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Section: Introductionmentioning

confidence: 99%

Linking Data to Ontologies

Poggi

Lembo

Calvanese

et al. 2008

Lecture Notes in Computer Science

503

523

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“…Observe that Theorem 1 is phrased in terms of data complexity [65], which means that the query is held fixed. As mentioned by Kimelfeld et al [45], the evaluation of tree patterns becomes intractable if the query is given as part of the input.…”

Section: Theorem 1 [20]mentioning

confidence: 99%

Probabilistic XML: Models and Complexity

Kimelfeld

Senellart

2013

Advances in Probabilistic Databases for Uncertain Information Management

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Abstract. Uncertainty in data naturally arises in various applications, such as data integration and Web information extraction. Probabilistic XML is one of the concepts that have been proposed to model and manage various kinds of uncertain data. In essence, a probabilistic XML document is a compact representation of a probability distribution over ordinary XML documents. Various models of probabilistic XML provide different languages, with various degrees of expressiveness, for such compact representations. Beyond representation, probabilistic XML systems are expected to support data management in a way that properly reflects the uncertainty. For instance, query evaluation entails probabilistic inference, and update operations need to properly change the entire probability space. Efficiently and effectively accomplishing data-management tasks in that manner is a major technical challenge. This chapter reviews the literature on probabilistic XML. Specifically, this chapter discusses the probabilistic XML models that have been proposed, and the complexity of query evaluation therein. Also discussed are other data-management tasks like updates and compression, as well as systemic and implementation aspects.

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“…Theorem 17 (Immerman [8], Vardi [20]) A problem is in P if, and only if, it can be defined by a sentence of FO s (IFP). Moreover, any sentence of FO s (IFP) is logically equivalent to one of the form [IFP R,x ϕ](max), where ϕ is quantifier-free first-order and max is a tuple every component of which is the constant symbol max.…”

Section: Inflationary Fixed-point Logicmentioning

confidence: 99%

Frameworks for Logically Classifying Polynomial-Time Optimisation Problems

Gate

Stewart

2010

Computer Science – Theory and Applications

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract We show that a logical framework, based around a fragment of existential second-order logic formerly proposed by others so as to capture the class of polynomially-bounded P-optimisation problems, cannot hope to do so, under the assumption that P = NP. We do this by exhibiting polynomially-bounded maximisation and minimisation problems that can be expressed in the framework but whose decision versions are NPcomplete. We propose an alternative logical framework, based around inflationary fixed-point logic, and show that we can capture the above classes of optimisation problems. We use the inductive depth of an inflationary fixed-point as a means to describe the objective functions of the instances of our optimisation problems.

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The complexity of relational query languages (Extended Abstract)

Cited by 1,019 publications

References 18 publications

Linking Data to Ontologies

Linking Data to Ontologies

Probabilistic XML: Models and Complexity

Frameworks for Logically Classifying Polynomial-Time Optimisation Problems

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