1,557 research outputs found

    XMG : eXtending MetaGrammars to MCTAG

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    In this paper, we introduce an extension of the XMG system (eXtensibleMeta-Grammar) in order to allow for the description of Multi-Component Tree Adjoining Grammars. In particular, we introduce the XMG formalism and its implementation, and show how the latter makes it possible to extend the system relatively easily to different target formalisms, thus opening the way towards multi-formalism.Dans cet article, nous présentons une extension du système XMG (eXtensible MetaGrammar) afin de permettre la description de grammaires darbres adjoints à composantes multiples. Nous présentons en particulier le formalisme XMG et son implantation et montrons comment celle-ci permet relativement aisément détendre le système à différents formalismes grammaticaux cibles, ouvrant ainsi la voie au multi-formalisme

    Programmiersprachen und Rechenkonzepte

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    Seit 1984 veranstaltet die GI--Fachgruppe "Programmiersprachen und Rechenkonzepte" regelmäßig im Frühjahr einen Workshop im Physikzentrum Bad Honnef. Das Treffen dient in erster Linie dem gegenseitigen Kennenlernen, dem Erfahrungsaustausch, der Diskussion und der Vertiefung gegenseitiger Kontakte

    Validation Framework for RDF-based Constraint Languages

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    In this thesis, a validation framework is introduced that enables to consistently execute RDF-based constraint languages on RDF data and to formulate constraints of any type. The framework reduces the representation of constraints to the absolute minimum, is based on formal logics, consists of a small lightweight vocabulary, and ensures consistency regarding validation results and enables constraint transformations for each constraint type across RDF-based constraint languages

    Survey over Existing Query and Transformation Languages

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    A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability of many current Semantic Web approaches to cope with data available in such diverging representation formalisms as XML, RDF, or Topic Maps. A common query language is the first step to allow transparent access to data in any of these formats. To further the understanding of the requirements and approaches proposed for query languages in the conventional as well as the Semantic Web, this report surveys a large number of query languages for accessing XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from all these areas. From the detailed survey of these query languages, a common classification scheme is derived that is useful for understanding and differentiating languages within and among all three areas

    Fabular: regression formulas as probabilistic programming

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    Regression formulas are a domain-specific language adopted by several R packages for describing an important and useful class of statistical models: hierarchical linear regressions. Formulas are succinct, expressive, and clearly popular, so are they a useful addition to probabilistic programming languages? And what do they mean? We propose a core calculus of hierarchical linear regression, in which regression coefficients are themselves defined by nested regressions (unlike in R). We explain how our calculus captures the essence of the formula DSL found in R. We describe the design and implementation of Fabular, a version of the Tabular schema-driven probabilistic programming language, enriched with formulas based on our regression calculus. To the best of our knowledge, this is the first formal description of the core ideas of R's formula notation, the first development of a calculus of regression formulas, and the first demonstration of the benefits of composing regression formulas and latent variables in a probabilistic programming language.Adam Åšcibior received travel support from the DARPA PPAML programme. Marcin Szymczak was supported by Microsoft Research through its PhD Scholarship Programme.This is the author accepted manuscript. The final version is available from the Association of Computer Machinery via http://dx.doi.org/10.1145/2837614.283765

    Satisfiability for SCULPT-Schemas for CSV-Like Data

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    SCULPT is a simple schema language inspired by the recent working effort towards a recommendation by the World Wide Web Consortium (W3C) for tabular data and metadata on the Web. In its core, a SCULPT schema consists of a set of rules where left-hand sides select sets of regions in the tabular data and the right-hand sides describe the contents of these regions. A document (divided in cells by row- and column-delimiters) then satisfies a schema if it satisfies every rule. In this paper, we study the satisfiability problem for SCULPT schemas. As SCULPT describes grid-like structures, satisfiability obviously becomes undecidable rather quickly even for very restricted schemas. We define a schema language called L-SCULPT (Lego SCULPT) that restricts the walking power of SCULPT by selecting rectangular shaped areas and only considers tables for which selected regions do not intersect. Depending on the axes used by L-SCULPT, we show that satisfiability is PTIME-complete or undecidable. One of the tractable fragments is practically useful as it extends the structural core of the current W3C proposal for schemas over tabular data. We therefore see how the navigational power of the W3C proposal can be extended while still retaining tractable satisfiability tests

    Efficient Analysis of Complex Diagrams using Constraint-Based Parsing

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    This paper describes substantial advances in the analysis (parsing) of diagrams using constraint grammars. The addition of set types to the grammar and spatial indexing of the data make it possible to efficiently parse real diagrams of substantial complexity. The system is probably the first to demonstrate efficient diagram parsing using grammars that easily be retargeted to other domains. The work assumes that the diagrams are available as a flat collection of graphics primitives: lines, polygons, circles, Bezier curves and text. This is appropriate for future electronic documents or for vectorized diagrams converted from scanned images. The classes of diagrams that we have analyzed include x,y data graphs and genetic diagrams drawn from the biological literature, as well as finite state automata diagrams (states and arcs). As an example, parsing a four-part data graph composed of 133 primitives required 35 sec using Macintosh Common Lisp on a Macintosh Quadra 700.Comment: 9 pages, Postscript, no fonts, compressed, uuencoded. Composed in MSWord 5.1a for the Mac. To appear in ICDAR '95. Other versions at ftp://ftp.ccs.neu.edu/pub/people/futrell

    IDEF3 formalization report

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    The Process Description Capture Method (IDEF3) is one of several Integrated Computer-Aided Manufacturing (ICAM) DEFinition methods developed by the Air Force to support systems engineering activities, and in particular, to support information systems development. These methods have evolved as a distillation of 'good practice' experience by information system developers and are designed to raise the performance level of the novice practitioner to one comparable with that of an expert. IDEF3 is meant to serve as a knowledge acquisition and requirements definition tool that structures the user's understanding of how a given process, event, or system works around process descriptions. A special purpose graphical language accompanying the method serves to highlight temporal precedence and causality relationships relative to the process or event being described

    How long, O Bayesian network, will I sample thee? A program analysis perspective on expected sampling times

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    Bayesian networks (BNs) are probabilistic graphical models for describing complex joint probability distributions. The main problem for BNs is inference: Determine the probability of an event given observed evidence. Since exact inference is often infeasible for large BNs, popular approximate inference methods rely on sampling. We study the problem of determining the expected time to obtain a single valid sample from a BN. To this end, we translate the BN together with observations into a probabilistic program. We provide proof rules that yield the exact expected runtime of this program in a fully automated fashion. We implemented our approach and successfully analyzed various real-world BNs taken from the Bayesian network repository
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