Search (31 results, page 1 of 2)

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Date

6. 8.2010 14:22:28

Year

2003

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Abstract

This book constitutes the refereed proceedings of the 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, held in Loughborough, UK in June 2003. The 81 revised full papers presented were carefully reviewed and selected from more than 140 submissions. Among the topics addressed are soft computing, fuzzy logic, diagnosis, knowledge representation, knowledge management, automated reasoning, machine learning, planning and scheduling, evolutionary computation, computer vision, agent systems, algorithmic learning, tutoring systems, financial analysis, etc.

RSWK

Künstliche Intelligenz / Kongress / Loughborough <2003>
Soft Computing / Kongress / Loughborough <2003>
Expertensystem / Kongress / Loughborough <2003>

Subject

Künstliche Intelligenz / Kongress / Loughborough <2003>
Soft Computing / Kongress / Loughborough <2003>
Expertensystem / Kongress / Loughborough <2003>

Year

2003

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Abstract

This paper is about the relationship between the topic map and RDF standards families. It compares the two technologies and looks at ways to make it easier for users to live in a world where both technologies are used. This is done by looking at how to convert information back and forth between the two technologies, how to convert schema information, and how to do queries across both information representations. Ways to achieve all of these goals are presented. This paper extends and improves on earlier work on the same subject, described in [Garshol01b]. This paper was first published in the proceedings of XML Europe 2003, 5-8 May 2003, organized by IDEAlliance, London, UK.

Year

2003

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Issue

W3C Note 11 June 2003.

Year

2003

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Source

The Semantic Web - ISWC 2003. Eds. D. Fensel et al

Year

2003

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Source

Cataloging and classification quarterly. 37(2003) nos.1/2, S.187-203

Year

2003

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Year

2003

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Source

Journal of Biomedical Informatics, 36(2003) no.6), S.462-477

Year

2003

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Content

Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

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Date

26.12.2011 13:22:07

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Date

30. 5.2010 16:22:35

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Year

2003

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Date

31. 7.2010 16:58:22

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Date

14. 8.2011 13:33:22

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Date

22. 1.2016 17:47:06

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Date

11. 2.2011 18:22:58

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Date

11. 2.2011 18:22:25

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Abstract

Linguists in the structuralist tradition (e.g., Lyons, 1977; Saussure, 1959) have asserted that concepts cannot be defined on their own but only in relation to other concepts. Semantic relations appear to reflect a logical structure in the fundamental nature of thought (Caplan & Herrmann, 1993). Green, Bean, and Myaeng (2002) noted that semantic relations play a critical role in how we represent knowledge psychologically, linguistically, and computationally, and that many systems of knowledge representation start with a basic distinction between entities and relations. Green (2001, p. 3) said that "relationships are involved as we combine simple entities to form more complex entities, as we compare entities, as we group entities, as one entity performs a process on another entity, and so forth. Indeed, many things that we might initially regard as basic and elemental are revealed upon further examination to involve internal structure, or in other words, internal relationships." Concepts and relations are often expressed in language and text. Language is used not just for communicating concepts and relations, but also for representing, storing, and reasoning with concepts and relations. We shall examine the nature of semantic relations from a linguistic and psychological perspective, with an emphasis on relations expressed in text. The usefulness of semantic relations in information science, especially in ontology construction, information extraction, information retrieval, question-answering, and text summarization is discussed. Research and development in information science have focused on concepts and terms, but the focus will increasingly shift to the identification, processing, and management of relations to achieve greater effectiveness and refinement in information science techniques. Previous chapters in ARIST on natural language processing (Chowdhury, 2003), text mining (Trybula, 1999), information retrieval and the philosophy of language (Blair, 2003), and query expansion (Efthimiadis, 1996) provide a background for this discussion, as semantic relations are an important part of these applications.

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Abstract

Mit der Verbreitung des Internets und insbesondere mit der Einführung des Begriffes Semantic Web wurde eine Reihe von neuen Begriffen (Termini) für nicht immer neue Entwicklungen eingeführt, ohne dass die bisherige Begriffsbildung bzw. die schon angewandten Lösungen in benachbarten Fachgebieten hinreichend berücksichtigt wurden. Dabei wird manchmal der Eindruck erweckt, dass die populären Anwendungszweige der Informatik (oder auch der Informationswissenschaft) hauptsächlich durch wirksame Schlagworte gesteuert werden. Im deutschsprachigen Raum kommt auch noch die oftmals (vermeintlich) werbewirksame Verwendung der nicht übersetzten englischen Ausdrücke im Original oder als eingedeutschter Termini. Letzteres führt dabei nicht selten zur semantischen Verschiebungen der Bedeutung der ursprünglichen Begriffe. So z.B. wird das englische Wort concept (entspricht dem deutschen Wort Begriff) mit allen seinen Ableitungen (wie z.B. conceptualization - Verbegrifflichung, conceptual - begrifflich) in der eingedeutschten unübersetzten Form fälschlich verwendet, ohne dass diese Wortschöpfungen dabei näher erläutert werden. Es wird dadurch der Eindruck erweckt, dass etwas inhaltlich Neues eingeführt wird. Häufig werden diese Begriffe auch nebeneinander verwendet, wie z.B. in der Definition von Ontologie in der Internet-Enzyklopädie Wikipedia " ... System von Begriffen und/oder Konzepten und Relationen zwischen diesen Begriffen". In den zahlreichen Studien über die Ontologie wird auf die Möglichkeit ähnlicher Verwendung von Thesauri nicht eingegangen, sie existieren im Kontext der Veröffentlichung überhaupt nicht (vgl. z.B. die Studie von Smith (2003), die jedoch mit Bezug zu Philosophie gerade zu überfrachtet wird). In der folgenden Arbeit werden verwandte Repräsentationsarten, wie z.B. Thesaurus, semantisches Netz, Frames, Themenkarten (Topic Maps) und Ontologie definiert. Die Gemeinsamkeiten dieser Repräsentationsformen werden dabei im Vordergrund stehen. Die in der Literatur häufig betonten Unterschiede sind manchmal aus der Unkenntnis der theoretischen Basis dieser Ansätze abzuleiten. Eine Koexistenz jeweiliger Repräsentation ist vonnöten. Im Vordergrund des Aufsatzes steht die mögliche Wechselwirkung zwischen Ontologien und Thesauri.

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Abstract

Unternehmen sehen sich heutzutage regelmäßig der Herausforderung gegenübergestellt, aus umfangreichen Mengen an Dokumenten schnell relevante Informationen zu identifizieren. Dabei zeigt sich jedoch, dass Suchverfahren, die lediglich syntaktische Abgleiche von Informationsbedarfen mit potenziell relevanten Dokumenten durchführen, häufig nicht die an sie gestellten Erwartungen erfüllen. Viel versprechendes Potenzial bietet hier der Einsatz von Ontologien für das Information Retrieval. Beim ontologiebasierten Information Retrieval werden Ontologien eingesetzt, um Wissen in einer Form abzubilden, die durch Informationssysteme verarbeitet werden kann. Eine Berücksichtigung des so explizierten Wissens durch Suchalgorithmen führt dann zu einer optimierten Deckung von Informationsbedarfen. Jan Hermans stellt in seinem Buch ein adaptives Referenzmodell für die Entwicklung von ontologiebasierten Information Retrieval-Systemen vor. Zentrales Element seines Modells ist die einsatzkontextspezifische Adaption des Retrievalprozesses durch bewährte Techniken, die ausgewählte Aspekte des ontologiebasierten Information Retrievals bereits effektiv und effizient unterstützen. Die Anwendung des Referenzmodells wird anhand eines Fallbeispiels illustriert, bei dem ein Information Retrieval-System für die Suche nach Open Source-Komponenten entwickelt wird. Das Buch richtet sich gleichermaßen an Dozenten und Studierende der Wirtschaftsinformatik, Informatik und Betriebswirtschaftslehre sowie an Praktiker, die die Informationssuche im Unternehmen verbessern möchten. Jan Hermans, Jahrgang 1978, studierte Wirtschaftsinformatik an der Westfälischen Wilhelms-Universität in Münster. Seit 2003 war er als Wissenschaftlicher Mitarbeiter am European Research Center for Information Systems der WWU Münster tätig. Seine Forschungsschwerpunkte lagen in den Bereichen Wissensmanagement und Information Retrieval. Im Mai 2008 erfolgte seine Promotion zum Doktor der Wirtschaftswissenschaften.