Logical Foundations of Object-Oriented and Frame-Based Languages

We propose a novel logic, called Frame Logic (abbr., F-logic), that accounts in a clean, declarative fashion for most of the structural aspects of object-oriented and frame-based languages. These features include object identity, complex objects, inheritance, polymorphic types, methods, encapsulation, and others. In a sense, F-logic stands in the same relationship to the object-oriented paradigm as classical predicate calculus stands to relational programming. The syntax of F-logic is higher-order, which, among other things, allows the user to explore data and schema using the same declarative language. F-logic has a model-theoretic semantics and a sound and complete resolution-based proof procedure. This paper also discusses various aspects of programming in declarative object-oriented languages based on F-logic

Ontology-based Information Extraction with SOBA

In this paper we describe SOBA, a sub-component of the SmartWeb multi-modal dialog system. SOBA is a component for ontologybased information extraction from soccer web pages for automatic population of a knowledge base that can be used for domainspecific question answering. SOBA realizes a tight connection between the ontology, knowledge base and the information extraction component. The originality of SOBA is in the fact that it extracts information from heterogeneous sources such as tabular structures, text and image captions in a semantically integrated way. In particular, it stores extracted information in a knowledge base, and in turn uses the knowledge base to interpret and link newly extracted information with respect to already existing entities

Approximate OWL-Reasoning with Screech

Applications of expressive ontology reasoning for the Semantic Web require scalable algorithms for deducing implicit knowledge from explicitly given knowledge bases. Besides the development of more effi- cient such algorithms, awareness is rising that approximate reasoning solutions will be helpful and needed for certain application domains. In this paper, we present a comprehensive overview of the Screech approach to approximate reasoning with OWL ontologies, which is based on the KAON2 algorithms, facilitating a compilation of OWL DL TBoxes into Datalog, which is tractable in terms of data complexity. We present three different instantiations of the Screech approach, and report on experiments which show that a significant gain in efficiency can be achieved

Développement récents en matière de conception, de maintenance et d’utilisation des ontologies

Le présent article offre une synthèse des développements récents survenus dans le domaine de l’ingénierie ontologique: les bases théoriques, les ontologies les plus connues, les méthodologies et les environnements logiciels disponibles pour la création d’ontologies, ainsi que l’utilisation d’ontologies dans des applications à des fins commerciales et de recherche

An Overview of F-OML: An F-Logic Based Object Modeling Language

F-OML is an F-Logic based Object Modeling Language. It can be used for extending UML diagrams, reasoning about them, testing UML models, and defining their syntax (meta-modeling) and semantics. This wide range of applications of F-OML stems from several language features, including polymorphism, multi-level object modeling, and model instantiation. F-OML supports modeling of classes and properties. F-OML is layered on top of an elegant formal language of guarded path expressions, called PathLP, which is used to define objects and their types. PathLP is a logic programming language, inspired by F-logic. It supports path expressions, rules, constraints, and queries, and it is easy to implement by translation into a tabling Prolog engine, such as XSB. In this short overview we informally describe the main constructs of PathLP and F-OML, and provide examples that demonstrate the four modes of F-OML usage. Formal definitions and additional details are found in the full paper. Finally, we analyze how language features contribute to its expressiveness, and provide a brief comparison with OCL

Guidelines to Study Differences in Expressiveness between Ontology Specification Languages: A Case Of Study

We focus on our experiences on translating ontologies between two ontology languages, FLogic and Ontolingua, in the framework of Methontology and ODE. Rather than building "ad hoc" translators between languages or using KIF, our option consists of translating through ODE intermediate representations. So, we have built direct translators from ODE intermediate representations to Ontolingua and FLogic, and we have also built reverse translators from these two languages to ODE intermediate representations. Expressiveness of the target languages is the main feature to analyse when automatically generating ontologies from ODE intermediate representations. Therefore, we analyse the expressiveness of Ontolingua and FLogic for creating classes, instances, relations, functions and axioms, which are the essential components in ontologies. The motivation for this analysis can be found in the (KA)² initiative and can be easily extended to any other domains and languages

A procedure for mediation of queries to sources in disparate contexts

Includes bibliographical references (p. 17-19).S. Bressan ... [et al.]

Evaluating Knowledge Representation and Reasoning Capabilites of Ontology Specification Languages

The interchange of ontologies across the World Wide Web (WWW) and the cooperation among heterogeneous agents placed on it is the main reason for the development of a new set of ontology specification languages, based on new web standards such as XML or RDF. These languages (SHOE, XOL, RDF, OIL, etc) aim to represent the knowledge contained in an ontology in a simple and human-readable way, as well as allow for the interchange of ontologies across the web. In this paper, we establish a common framework to compare the expressiveness of "traditional" ontology languages (Ontolingua, OKBC, OCML, FLogic, LOOM) and "web-based" ontology languages. As a result of this study, we conclude that different needs in KR and reasoning may exist in the building of an ontology-based application, and these needs must be evaluated in order to choose the most suitable ontology language(s)

How to make it faster and at lower cost? B2B integration with semantic web services

Web services and service oriented architectures present a new approach to application integration. While it is reasonable inside an enterprise, it has certain deficiencies when applied in a B2B environment. This deficiencies apply to the discovery, invocation and composition phases, which require considerable manual effort. In the paper, we show on example of a mortgage simulator how these deficiencies can be overcome by applying-semantic web services. The application is compatible with the Web Services Modelling Ontology and makes use of an execution environment automating the processes of discovery, composition and invocation of semantic web services, enabling faster and cheaper B2B application integration