Magic Sets for Disjunctive Datalog Programs

In this paper, a new technique for the optimization of (partially) bound queries over disjunctive Datalog programs with stratified negation is presented. The technique exploits the propagation of query bindings and extends the Magic Set (MS) optimization technique. An important feature of disjunctive Datalog is nonmonotonicity, which calls for nondeterministic implementations, such as backtracking search. A distinguishing characteristic of the new method is that the optimization can be exploited also during the nondeterministic phase. In particular, after some assumptions have been made during the computation, parts of the program may become irrelevant to a query under these assumptions. This allows for dynamic pruning of the search space. In contrast, the effect of the previously defined MS methods for disjunctive Datalog is limited to the deterministic portion of the process. In this way, the potential performance gain by using the proposed method can be exponential, as could be observed empirically. The correctness of MS is established thanks to a strong relationship between MS and unfounded sets that has not been studied in the literature before. This knowledge allows for extending the method also to programs with stratified negation in a natural way. The proposed method has been implemented in DLV and various experiments have been conducted. Experimental results on synthetic data confirm the utility of MS for disjunctive Datalog, and they highlight the computational gain that may be obtained by the new method w.r.t. the previously proposed MS methods for disjunctive Datalog programs. Further experiments on real-world data show the benefits of MS within an application scenario that has received considerable attention in recent years, the problem of answering user queries over possibly inconsistent databases originating from integration of autonomous sources of information.Comment: 67 pages, 19 figures, preprint submitted to Artificial Intelligenc

Constraint-based Query Distribution Framework for an Integrated Global Schema

Distributed heterogeneous data sources need to be queried uniformly using global schema. Query on global schema is reformulated so that it can be executed on local data sources. Constraints in global schema and mappings are used for source selection, query optimization,and querying partitioned and replicated data sources. The provided system is all XML-based which poses query in XML form, transforms, and integrates local results in an XML document. Contributions include the use of constraints in our existing global schema which help in source selection and query optimization, and a global query distribution framework for querying distributed heterogeneous data sources.Comment: The Proceedings of the 13th INMIC 2009), Dec. 14-15, 2009, Islamabad, Pakistan. Pages 1 - 6 Print ISBN: 978-1-4244-4872-2 INSPEC Accession Number: 11072575 Date of Current Version : 15 January 201

Some DLV Applications for Knowledge Management

Abstract. Even if the industrial exploitation of the DLV system has started very recently, DLV already has a history of applications on the industrial level. The most valuable applications from a commercial viewpoint are those in the area of Knowledge Management. They have been realized by the company EXEURA s.r.l. -a spin-off company of the University of Calabria having a branch also in Chicago -with the support of the DLVSYSTEM s.r.l.. DLV applications in this area have not been realized directly, but through some specializations of DLV into Knowledge Management (KM) products for Text Classification, Information Extraction, and Ontology Representation and Reasoning. After briefly describing these KM products, we report on their recently-released successful applications

On the evolution of the instance level of DL-lite knowledge bases

Recent papers address the issue of updating the instance level of knowledge bases expressed in Description Logic following a model-based approach. One of the outcomes of these papers is that the result of updating a knowledge base K is generally not expressible in the Description Logic used to express K. In this paper we introduce a formula-based approach to this problem, by revisiting some research work on formula-based updates developed in the '80s, in particular the WIDTIO (When In Doubt, Throw It Out) approach. We show that our operator enjoys desirable properties, including that both insertions and deletions according to such operator can be expressed in the DL used for the original KB. Also, we present polynomial time algorithms for the evolution of the instance level knowledge bases expressed in the most expressive Description Logics of the DL-lite family

Unit Testing in ASPIDE

Answer Set Programming (ASP) is a declarative logic programming formalism, which is employed nowadays in both academic and industrial real-world applications. Although some tools for supporting the development of ASP programs have been proposed in the last few years, the crucial task of testing ASP programs received less attention, and is an Achilles' heel of the available programming environments. In this paper we present a language for specifying and running unit tests on ASP programs. The testing language has been implemented in ASPIDE, a comprehensive IDE for ASP, which supports the entire life-cycle of ASP development with a collection of user-friendly graphical tools for program composition, testing, debugging, profiling, solver execution configuration, and output-handling.Comment: 12 pages, 4 figures, Proceedings of the 25th Workshop on Logic Programming (WLP 2011