Relations and Transductions Realized by Restarting Automata

Gegenstand der vorliegenden Arbeit ist die Analyse verschiedener Formalismen zur Berechnung binärer Wortrelationen. Dabei ist die Grundlage aller hier ausgeführten Betrachtungen das Modell der Restart-Automaten, welches 1995 von Jancar et. al. eingeführt wurde. Zum einen wird das bereits für Restart-Automaten bekannte Konzept der input/output- und proper-Relationen weiterführend untersucht, sowie auf Systeme von zwei parallel arbeitenden und miteinander kommunizierenden Restart-Automaten (PC-Systeme) erweitert. Zum anderen wird eine Variante der Restart-Automaten eingeführt, die sich an klassischen Automatenmodellen zur Berechnung von Relationen orientiert. Mit Hilfe dieser Mechanismen kann gezeigt werden, dass einige Klassen, die durch input/output- und proper-Relationen von Restart Automaten definiert werden, mit den traditionellen Relationsklassen der Rationalen Relationen und der Pushdown-Relationen übereinstimmen. Weiterhin stellt sich heraus, dass das Konzept der parallel kommunizierenden Automaten äußerst mächtig ist, da bereits die Klasse der proper-Relationen von monotonen PC-Systemen alle berechenbaren Relationen umfasst. Der Haupteil der Arbeit beschäftigt sich mit den so genannten Restart-Transducern, welche um eine Ausgabefunktion erweiterte Restart-Automaten sind. Es zeigt sich, dass sich insbesondere dieses Modell mit seinen verschiedenen Erweiterungen und Einschränkungen dazu eignet, eine umfassende Hierarchie von Relationsklassen zu etablieren. In erster Linie seien hier die verschiedenen Typen von monotonen Restart-Transducern erwähnt, mit deren Hilfe viele interessante neue und bekannte Relationsklassen innerhalb der längenbeschränkten Pushdown-Relationen charakterisiert werden. Abschließend wird, im Kontrast zu den vorhergehenden Modellen, das nicht auf Restart-Automaten basierende Konzept des Übersetzens durch Beobachtung ("Transducing by Observing") zur Relationsberechnung eingeführt. Dieser, den Restart-Transducern nicht unähnliche Mechanismus, wird im weitesten Sinne dazu genutzt, einen anderen Blickwinkel auf die von Restart-Transducern definierten Relationen einzunehmen, sowie eine obere Schranke für die Berechnungskraft der Restart-Transducer zu gewinnen.

Context Mediation in the Semantic Web: Handling OWL Ontology and Data Disparity through Context Interchange

The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Web – both at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Reasoning about Temporal Context using Ontology and Abductive Constraint Logic Programming

The underlying assumptions for interpreting the meaning of data often change over time, which further complicates the problem of semantic heterogeneities among autonomous data sources. As an extension to the COntext INterchange (COIN) framework, this paper introduces the notion of temporal context as a formalization of the problem. We represent temporal context as a multi-valued method in F-Logic; however, only one value is valid at any point in time, the determination of which is constrained by temporal relations. This representation is then mapped to an abductive constraint logic programming framework with temporal relations being treated as constraints. A mediation engine that implements the framework automatically detects and reconciles semantic differences at different times. We articulate that this extended COIN framework is suitable for reasoning on the Semantic Web.

Industrial Relations and "Humanware"

This is a preliminary paper. Please do not quote without the permission of the author. The research on which this paper is based has been conducted with the collaboration of John Paul MacDuffie, MIT. The researchers owe much to the warm cooperation of managers, employees, and union officials of Japanese auto companies and joint venture companies in the U.S. as well as American auto companies and the UAW. We would like to express our sincere appreciation for their assistance.

Supplier Relations in Japan and the United States

This working paper was originally printed in the Working Paper Series of the MIT International Motor Vehicle Program

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 13: Web Technologies 2 - The Semantic Web

The semantic web represents a current research effort to increase the capability of machines to make sense of content on the web. In this class, Peter Scheir will give a guest lecture on the basic principles underlying the semantic web vision, including RDF, OWL and other standards.

Introduction to the Semantic Web and the Web of Linked Data

Presentation given as part of the EPrints/dotAC training event on 26 Mar 2010.