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Characterizing and Computing Semantically Correct Answers from Databases with Annotated Logic and Answer Sets
"... A relational database may not satisfy certain integrity constraints (ICs) for several reasons. However most likely most of the information in it is still consistent with the ICs. The answers to queries that are consistent with the ICs can be considered sematically correct answers, and are characteri ..."
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Cited by 35 (23 self)
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A relational database may not satisfy certain integrity constraints (ICs) for several reasons. However most likely most of the information in it is still consistent with the ICs. The answers to queries that are consistent with the ICs can be considered sematically correct answers, and are characterized [2] as ordinary answers that can be obtained from every minimally repaired version of the database. In this paper we address the problem of specifying those repaired versions as the minimal models of a theory written in Annotated Predicate Logic [27]. It is also shown how to specify database repairs using disjunctive logic program with annotation arguments and a classical stable model semantics.
Preferred Answer Sets for Ordered Logic Programs
 In European Conference on Logics for Artificial Intelligence (JELIA
, 2002
"... We extend answer set semantics to deal with inconsistent programs (containing classical negation), by finding a "best" answer set. Within the context of inconsistent programs, it is natural to have a partial order on rules, representing a preference for satisfying certain rules, possibl ..."
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Cited by 34 (8 self)
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We extend answer set semantics to deal with inconsistent programs (containing classical negation), by finding a "best" answer set. Within the context of inconsistent programs, it is natural to have a partial order on rules, representing a preference for satisfying certain rules, possibly at the cost of violating less important ones. We show that such a rule order induces a natural order on extended answer sets, the minimal elements of which we call preferred answer sets. We characterize the expressiveness of the resulting semantics and show that it can simulate negation as failure as well as disjunction. We illustrate an application of the approach by considering database repairs, where minimal repairs are shown to correspond to preferred answer sets.
Scalar Aggregation in Inconsistent Databases
, 2003
"... We consider herescalq aggregation queries in databases that mayviolzz a given set of functional dependencies. We de#ne consistent answers to such queries to begreatestlEzqglzqgl upper bounds on thevalq of thescalW function acrossal (minimal repairs of the database. We show how to compute such answe ..."
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Cited by 34 (5 self)
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We consider herescalq aggregation queries in databases that mayviolzz a given set of functional dependencies. We de#ne consistent answers to such queries to begreatestlEzqglzqgl upper bounds on thevalq of thescalW function acrossal (minimal repairs of the database. We show how to compute such answers. We provide acomplWg characterization of thecomputational compltati of thisproblz Wealf show howtractabilfx can be improved inseveral special cases (oneinvolfz anovel applNgjfzz of BoyceCoddNormal Form) and present apractical hybrid queryevalq###x method.
Magic Sets and their Application to Data Integration
 In Proc. International Conference on Database Theory (ICDT 05), Springer LNCS 3363, 2005
, 2005
"... Abstract. We propose a generalization of the wellknown Magic Sets technique to Datalog ¬ programs with (possibly unstratified) negation under stable model semantics. Our technique produces a new program whose evaluation is generally more efficient (due to a smaller instantiation), while preserving ..."
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Cited by 32 (8 self)
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Abstract. We propose a generalization of the wellknown Magic Sets technique to Datalog ¬ programs with (possibly unstratified) negation under stable model semantics. Our technique produces a new program whose evaluation is generally more efficient (due to a smaller instantiation), while preserving soundness under cautious reasoning. Importantly, if the original program is consistent, then full queryequivalence is guaranteed for both brave and cautious reasoning, which turn out to be sound and complete. In order to formally prove the correctness of our Magic Sets transformation, we introduce a novel notion of modularity for Datalog ¬ under the stable model semantics, which is relevant per se. We prove that a module can be evaluated independently from the rest of the program, while preserving soundness under cautious reasoning. For consistent programs, both soundness and completeness are guaranteed for brave reasoning and cautious reasoning as well. Our Magic Sets optimization constitutes an effective method for enhancing the performance of dataintegration systems in which queryanswering is carried out by means of cautious reasoning over Datalog ¬ programs. In fact, preliminary results of experiments in the EU project INFOMIX, show that Magic Sets are fundamental for the scalability of the system. 1
On the Computational Complexity of MinimalChange Integrity Maintenance in Relational Databases
 IN BERTOSSI ET AL
, 2004
"... We address the problem of minimalchange integrity maintenance in the context of integrity constraints in relational databases. Using the framework proposed by Arenas, Bertossi, and Chomicki [4], we focus on two basic computational issues: repair checking (is a database instance a repair of a given ..."
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Cited by 23 (4 self)
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We address the problem of minimalchange integrity maintenance in the context of integrity constraints in relational databases. Using the framework proposed by Arenas, Bertossi, and Chomicki [4], we focus on two basic computational issues: repair checking (is a database instance a repair of a given database?) and consistent query answers (is a tuple an answer to a given query in every repair of a given database?). We study the computational complexity of both problems, delineating the boundary between the tractable and the intractable. We review relevant semantical issues and survey different computational mechanisms proposed in this context. Our analysis sheds light on the computational feasibility of minimalchange integrity maintenance. The tractable cases should lead to practical implementations. The intractability results highlight the inherent limitations of any integrity enforcement mechanism, e.g., triggers or referential constraint actions, as a way of performing minimalchange integrity maintenance.
Repairing Databases with Annotated Predicate Logic
 Ninth International Workshop on NonMonotonic Reasoning (NMR02), Special Session: Changing and Integrating Information: From Theory to Practice
, 2002
"... Consistent answers from a relational database that violates a given set of integrity constraints are characterized [Arenas et al. 1999] as ordinary answers that can be obtained from every repaired version of the database. In this paper we address the problem of specifying the repairs of a database a ..."
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Cited by 16 (9 self)
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Consistent answers from a relational database that violates a given set of integrity constraints are characterized [Arenas et al. 1999] as ordinary answers that can be obtained from every repaired version of the database. In this paper we address the problem of specifying the repairs of a database as the minimal models of a theory written in Annotated Predicate Logic [Kifer et al. 1992a]. The specification is then transformed into a disjunctive logic program with annotation arguments and a stable model semantics. From the program, consistent answers to first order queries are obtained.
Querying and repairing inconsistent numerical databases
 IN PROC
, 2010
"... The problem of extracting consistent information from relational databases violating integrity constraints on numerical data is addressed. In particular, aggregate constraints defined as linear inequalities on aggregatesum queries on input data are considered. The notion of repair as consistent set ..."
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Cited by 14 (0 self)
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The problem of extracting consistent information from relational databases violating integrity constraints on numerical data is addressed. In particular, aggregate constraints defined as linear inequalities on aggregatesum queries on input data are considered. The notion of repair as consistent set of updates at attributevalue level is exploited, and the characterization of several datacomplexity issues related to repairing data and computing consistent query answers is provided. Moreover, a method for computing “reasonable” repairs of inconsistent numerical databases is provided, for a restricted but expressive class of aggregate constraints. Several experiments are presented, which assess the effectiveness of the proposed approach in reallife application scenarios.
Computing repairs for inconsistent databases
 In CODAS ’01
, 2001
"... The objective of this paper is to investigate the problems related to the extensional integration of information sources. In particular, we propose an approach for managing inconsistent databases, i.e. databases violating integrity constraints. The presence of inconsistent data can be resolved by ..."
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Cited by 11 (1 self)
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The objective of this paper is to investigate the problems related to the extensional integration of information sources. In particular, we propose an approach for managing inconsistent databases, i.e. databases violating integrity constraints. The presence of inconsistent data can be resolved by “repairing ” the database, i.e. by providing a computational mechanism that ensures obtaining consistent “scenarios ” of the information or by consistently answer to queries posed on an inconsistent set of data. In this paper we consider preferences among repairs and possible answers by introducing a partial order among them on the base of some preference criteria. More specifically, preferences are expressed by considering polynomial functions applied to repairs and returning real numbers. The goodness of a repair is measured by estimating how much it violates the desiderata conditions and a repair is preferred if it minimizes the value of the polynomial function used to express the preference criteria. The main contribution of this work consists in the proposal of a logic approach for querying and repairing inconsistent databases that extends previous works by aallowing to express and manage preference criteria. The approach here proposed allows to express reliability on the information sources and is also suitable for expressing decision and optimization problems. The introduction of preference criteria strongly reduces the number of feasible repairs and answers; for special classes of constraints and functions it gives a unique repair and answer. Work partially supported by a MURST grants under the projects “D2I” and ”Sistemi informatici Integrati a supporto di benchmarking di progetti ed interventi ad innovazione tecnologica in campo agroalimentare”. The first author is also supported by ICARCNR. 1
DYNAMIC MAGIC SETS FOR DISJUNCTIVE DATALOG PROGRAMS
"... Abstract. Answer set programming (ASP) is a powerful formalism for knowledge representation and common sense reasoning that allows disjunction in rule heads and nonmonotonic negation in bodies. Magic Sets are a technique for optimizing query answering over logic programs and have been originally def ..."
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Cited by 8 (5 self)
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Abstract. Answer set programming (ASP) is a powerful formalism for knowledge representation and common sense reasoning that allows disjunction in rule heads and nonmonotonic negation in bodies. Magic Sets are a technique for optimizing query answering over logic programs and have been originally defined for standard Datalog, that is, ASP without disjunction and negation. Essentially, the input program is rewritten in order to identify a subset of the program instantiation which is sufficient for answering the query. Dynamic Magic Sets (DMS) are an extension of this technique to ASP. The optimization provided by DMS can be exploited also during the nondeterministic phase of ASP systems. In particular, after some assumptions have been made during the computation, parts of the program may become irrelevant to a query (because of these assumptions). This allows for dynamic pruning of the search space, which may result in exponential performance gains. DMS has been implemented in the DLV system and experimental results confirm the effectiveness of the technique.