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Publications

Publications by Gabriel David

1991

SEMANTICS OF PROPERTY INHERITANCE IN A HIERARCHICAL SYSTEM WITH EXPLICIT NEGATION

Authors
DAVID, G; PORTO, A;

Publication
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE

Abstract
The purpose of this paper is to present a first step in a formal study of inheritance systems. The kind of systems considered are those that support overriding (all definitions being taken as defaults) and multiple inheritance. The overriding is based on the explicit statement of negative information. The basic entities are classes and properties. The system is hierarchic because it is made out of classes which are structured as a hierarchy. We consider both the basic case of properties restricted to atomic propositional formulas and their negations, and the extension to properties defined by rules in the Logic Programming style. A formal definition of hierarchic systems is given for which a model-theoretic 3-valued semantics is introduced. This semantics is explicitly stated in terms of sets of individuals. It defines the notion of interpretation, the characterization of models, and what is meant by validity of formulas in such structures. The inheritance mechanism is able to choose from a set of inherited default properties which ones mechanism be overriden in order to guarantee that the local program has a model. The notion of characteristic individuals of classes, introduced in our semantics, turns out to play a clarifying role of the relationship between semantic and syntactic aspects of inheritance systems.

1993

Inheritance in a Hierarchy of Theories

Authors
David, G; Porto, A;

Publication
Progress in Artificial Intelligence, 6th Portuguese Conference on Artificial Intelligence, EPIA '93, Porto, Portugal, October 6-8, 1993, Proceedings

Abstract
This paper1 contains a proposal for a knowledge representation formalism based on a taxonomy of theories. It aims at clarifying the notions of inheritance and dependency among properties and classes, which are mixed together in the “inheritance networks” formalism, while also providing more expressiveness. A model-theoretic semantics in terms of sets of individuals is presented, which is parametric on the characterization of specificity. The case most thoroughly presented is rule inheritance which builds on the assumption that only facts have the force to impose overriding. A double denotation for classes, corresponding to two nested sets, is the key for interpreting defaults and exceptions. The problem of ambiguity propagation in the resulting system is addressed in the context of a discussion of the relationship between it and inheritance nets. © Springer-Verlag Berlin Heidelberg 1993.

1991

Semantics of Property Inheritance in a Hierarchic System with Explicit Negation

Authors
David, G; Porto, A;

Publication
EPIA 91, 5th Portuguese Conference on Artificial Intelligence, Albufeira, Portugal, October 1-3, 1991, Proceedings

Abstract
The purpose of this paper is to present a first step in a formal study of inheritance systems. The kind of systems considered are those that support overriding (all definitions being taken as defaults) and multiple inheritance. The overriding is based on the explicit statement of negative information. The basic entities are classes and properties. The system is hierarchic because it is made out of classes which are structured as a hierarchy. We consider both the basic case of properties restricted to atomic propositional formulas and their negations, and the extension to properties defined by rules in the Logic Programming style. A formal definition of hierarchic systems is given for which a model-theoretic 3-valued semantics is in roduced. This semantics is explicitly stated in terms of sets of individuals. It defines the notion of interpretation, the characterization of models, and what is meant by validity of formulas in such structures. The inheritance mechanism is able to choose from a set of inherited default properties which ones must be overriden in order to guarantee that the local program has a model. The notion of characteristic individuals of classes, introduced in our semantics, turns out to play a clarifying role of the relationship between semantic and syntactic aspects of inheritance systems. © Springer-Verlag Berlin Heidelberg 1991.

2011

Transformation Rules for Model Migration in Relational Database Preservation

Authors
Rahman, AU; Ribeiro, C; David, G;

Publication
Proceedings of the 8th International Conference on Digital Preservation, iPRES 2011, Singapore, November 1-4, 2011

Abstract

2012

High-Dimensional Indexing for Video Retrieval

Authors
Calistru, C; Ribeiro, C; Davi, G;

Publication
Multimedia - A Multidisciplinary Approach to Complex Issues

Abstract

2004

A multimedia database workbench for content and context retrieval

Authors
Ribeiro, C; David, G; Calistru, C;

Publication
2004 IEEE 6TH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING

Abstract
Multimedia databases are extending the scope of traditional databases to handle the complex structure of multimedia objects. Models for multimedia information must include representations for the structure and content of several media in a form that allows flexibility in retrieval. Content-based retrieval is the main motivation behind recent research in multimedia databases. The task of searching in video and audio content is made hard by the nature of audiovisual data where, unlike text, there is no direct syntactic channel between the object and its meaning [1]-[3]. We propose a model for multimedia content storage and retrieval accounting for both context and content information and taking advantage of their dependencies for effective retrieval. We then describe a prototype multimedia database with a retrieval interface. It has been used as a workbench for testing the representation model and integrating tools for feature extraction, information interchange and retrieval. The workbench allows an easy inclusion of new tools for content analysis and new methods for context- and content-based retrieval while offering storage and access for both the actual digital content and its metadata.

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