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Marc Gyssens

Bio: Marc Gyssens is an academic researcher from University of Antwerp. The author has contributed to research in topics: Query language & Relational database. The author has an hindex of 11, co-authored 17 publications receiving 571 citations.

Papers
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Journal ArticleDOI
TL;DR: A graph-oriented object database model (GOOD) is introduced as a theoretical basis for database systems in which manipulation as well as conceptual representation of data is transparently graph-based.
Abstract: A graph-oriented object database model (GOOD) is introduced as a theoretical basis for database systems in which manipulation as well as conceptual representation of data is transparently graph-based. In the GOOD model, the scheme as well as the instance of an object database is represented by a graph, and the data manipulation is expressed by graph transformations. These graph transformations are described using five basic operations and a method construct, all with a natural semantics. The basic operations add and delete objects and edges as a function of the matchings of a pattern. The expressiveness of the model in terms of object-oriented modeling and data manipulation power is investigated. >

161 citations

Book ChapterDOI
01 Jan 1984
TL;DR: A methodology is given to decompose a join dependency defined on a given relation scheme and it works for acyclic as well as for cyclic join dependencies.
Abstract: A methodology is given to decompose a join dependency defined on a given relation scheme. The methodology works for acyclic as well as for cyclic join dependencies.

66 citations

Journal ArticleDOI
01 Jun 1988
TL;DR: It is shown that the algebras obtained in this way are equivalent to a slight extension of the powerset algebra, thus emphasizing both the strength and the naturalness of thepowerset algebra as a tool to manipulate nested relations, and indicating more direct ways to implement this algebra.
Abstract: In this paper, we discuss augmentations of the nested relational algebra with programming constructs, such as while-loops and for-loops. We show that the algebras obtained in this way are equivalent to a slight extension of the powerset algebra, thus emphasizing both the strength and the naturalness of the powerset algebra as a tool to manipulate nested relations, and, at the same time, indicating more direct ways to implement this algebra.

58 citations

Journal ArticleDOI
TL;DR: It is shown how the technique of decomposition can be used to make integrity checking more efficient and generalize a well-known characterization for acyclic jds by proving that n-cyclicity is equivalent to “n-wise consistency implies global consistency.”
Abstract: In [10] a method is proposed for decomposing join dependencies (jds) in a relational database using the notion of a hinge. This method was subsequently studied in [11] and [12]. We show how the technique of decomposition can be used to make integrity checking more efficient. It turns out that it is important to find a decomposition that minimizes the number of edges of its largest element. We show that the decompositions obtained with the method described in [10] are optimal in this respect. This minimality criterion leads to the definition of the degree of cyclicity, which allows us to classify jds and leads to the notion of n-cyclicity, of which acyclicity is a special case for n = 2. We then show that, for a fixed value of n (which may be greater than 2). integrity checking can be performed in polynomial time provided we restrict ourselves to n-cyclic jds. Finally, we generalize a well-known characterization for acyclic jds by proving that n-cyclicity is equivalent to “n-wise consistency implies global consistency.” As a consequence, consistency checking can be performed in polynomial time if we restrict ourselves to n-cyclic jds, for a tired value of n, not necessarily equal to 2.

53 citations

Book ChapterDOI
01 May 1989
TL;DR: The expressive power of the Languages for models of nested relations and complex objects is described in terms of the three common types of completeness: calculus-completeness, BP- completeness and CH-completteness.
Abstract: Languages for models of nested relations and complex objects have been attracting considerable attention recently. Some of these languages are algebraic, others are calculus based, some are logic programming oriented. This paper describes these languages and surveys recent results about the expressive power of these languages. The emphasis is on completeness issues. The expressive power of the languages is described in terms of the three common types of completeness: calculus-completeness, BP-completeness and CH-completeness.

48 citations


Cited by
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Journal ArticleDOI
TL;DR: The main objective of this survey is to present the work that has been conducted in the area of graph database modeling, concentrating on data structures, query languages, and integrity constraints.
Abstract: Graph database models can be defined as those in which data structures for the schema and instances are modeled as graphs or generalizations of them, and data manipulation is expressed by graph-oriented operations and type constructors. These models took off in the eighties and early nineties alongside object-oriented models. Their influence gradually died out with the emergence of other database models, in particular geographical, spatial, semistructured, and XML. Recently, the need to manage information with graph-like nature has reestablished the relevance of this area. The main objective of this survey is to present the work that has been conducted in the area of graph database modeling, concentrating on data structures, query languages, and integrity constraints.

1,669 citations

Book
01 Jan 2006
TL;DR: Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.
Abstract: Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics. The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area. The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas. The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming. - Covers the whole field of constraint programming - Survey-style chapters - Five chapters on applications Table of Contents Foreword (Ugo Montanari) Part I : Foundations Chapter 1. Introduction (Francesca Rossi, Peter van Beek, Toby Walsh) Chapter 2. Constraint Satisfaction: An Emerging Paradigm (Eugene C. Freuder, Alan K. Mackworth) Chapter 3. Constraint Propagation (Christian Bessiere) Chapter 4. Backtracking Search Algorithms (Peter van Beek) Chapter 5. Local Search Methods (Holger H. Hoos, Edward Tsang) Chapter 6. Global Constraints (Willem-Jan van Hoeve, Irit Katriel) Chapter 7. Tractable Structures for CSPs (Rina Dechter) Chapter 8. The Complexity of Constraint Languages (David Cohen, Peter Jeavons) Chapter 9. Soft Constraints (Pedro Meseguer, Francesca Rossi, Thomas Schiex) Chapter 10. Symmetry in Constraint Programming (Ian P. Gent, Karen E. Petrie, Jean-Francois Puget) Chapter 11. Modelling (Barbara M. Smith) Part II : Extensions, Languages, and Applications Chapter 12. Constraint Logic Programming (Kim Marriott, Peter J. Stuckey, Mark Wallace) Chapter 13. Constraints in Procedural and Concurrent Languages (Thom Fruehwirth, Laurent Michel, Christian Schulte) Chapter 14. Finite Domain Constraint Programming Systems (Christian Schulte, Mats Carlsson) Chapter 15. Operations Research Methods in Constraint Programming (John Hooker) Chapter 16. Continuous and Interval Constraints(Frederic Benhamou, Laurent Granvilliers) Chapter 17. Constraints over Structured Domains (Carmen Gervet) Chapter 18. Randomness and Structure (Carla Gomes, Toby Walsh) Chapter 19. Temporal CSPs (Manolis Koubarakis) Chapter 20. Distributed Constraint Programming (Boi Faltings) Chapter 21. Uncertainty and Change (Kenneth N. Brown, Ian Miguel) Chapter 22. Constraint-Based Scheduling and Planning (Philippe Baptiste, Philippe Laborie, Claude Le Pape, Wim Nuijten) Chapter 23. Vehicle Routing (Philip Kilby, Paul Shaw) Chapter 24. Configuration (Ulrich Junker) Chapter 25. Constraint Applications in Networks (Helmut Simonis) Chapter 26. Bioinformatics and Constraints (Rolf Backofen, David Gilbert)

1,527 citations

Journal ArticleDOI
01 Jun 1989
TL;DR: In this paper, an object-based data model, whose structural part generalizes most of the known complex-object data models: cyclicity is allowed in both its schemas and instances, is presented.
Abstract: We demonstrate the power of object identities (oid's) as a database query language primitive. We develop an object-based data model, whose structural part generalizes most of the known complex-object data models: cyclicity is allowed in both its schemas and instances. Our main contribution is the operational part of the data model, the query language IQL, which uses oid's for three critical purposes: (1) to represent data-structures with sharing and cycles, (2) to manipulate sets and (3) to express any computable database query. IQL can be statically type checked, can be evaluated bottom-up and naturally generalizes most popular rule-based database languages. The model can also be extended to incorporate type inheritance, without changes to IQL. Finally, we investigate an analogous value-based data model, whose structural part is founded on regular infinite trees and whose operational part is IQL.

496 citations

Journal ArticleDOI
TL;DR: The different kinds of joins and the various implementation techniques are surveyed and they are classified based on how they partition tuples from different relations.
Abstract: The join operation is one of the fundamental relational database query operations. It facilitates the retrieval of information from two different relations based on a Cartesian product of the two relations. The join is one of the most diffidult operations to implement efficiently, as no predefined links between relations are required to exist (as they are with network and hierarchical systems). The join is the only relational algebra operation that allows the combining of related tuples from relations on different attribute schemes. Since it is executed frequently and is expensive, much research effort has been applied to the optimization of join processing. In this paper, the different kinds of joins and the various implementation techniques are surveyed. These different methods are classified based on how they partition tuples from different relations. Some require that all tuples from one be compared to all tuples from another; other algorithms only compare some tuples from each. In addition, some techniques perform an explicit partitioning, whereas others are implicit.

489 citations

Journal ArticleDOI
TL;DR: This paper proposes a new line of research where moving points and moving regions are viewed as 3-D (2-D space+time) or higher-dimensional entities whose structure and behavior is captured by modeling them as abstract data types.
Abstract: Spatio-temporal databases deal with geometries changing over time. In general, geometries cannot only change in discrete steps, but continuously, and we are talking about moving objects. If only the position in space of an object is relevant, then moving point is a basic abstraction; if also the extent is of interest, then the moving region abstraction captures moving as well as growing or shrinking regions. We propose a new line of research where moving points and moving regions are viewed as 3-D (2-D space+time) or higher-dimensional entities whose structure and behavior is captured by modeling them as abstract data types. Such types can be integrated as base (attribute) data types into relational, object-oriented, or other DBMS data models; they can be implemented as data blades, cartridges, etc. for extensible DBMSs. We expect these spatio-temporal data types to play a similarly fundamental role for spatio-temporal databases as spatial data types have played for spatial databases. The paper explains the approach and discusses several fundamental issues and questions related to it that need to be clarified before delving into specific designs of spatio- temporal algebras.

419 citations