Search (23 results, page 1 of 2)

  • × theme_ss:"Semantische Interoperabilität"
  • × theme_ss:"Wissensrepräsentation"
  • × type_ss:"a"
  1. Sigel, A.: Wissensorganisation, Topic Maps und Ontology Engineering : Die Verbindung bewährter Begriffsstrukturen mit aktueller XML Technologie (2004) 0.02 
    0.01721226 = product of:
  0.05163678 = sum of:
    0.008924231 = weight(_text_:in in 3236) [ClassicSimilarity], result of:
      0.008924231 = score(doc=3236,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.15028831 = fieldWeight in 3236, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3236)
    0.04271255 = weight(_text_:und in 3236) [ClassicSimilarity], result of:
      0.04271255 = score(doc=3236,freq=26.0), product of:
        0.09675359 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.043654136 = queryNorm
        0.441457 = fieldWeight in 3236, product of:
          5.0990195 = tf(freq=26.0), with freq of:
            26.0 = termFreq=26.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3236)
  0.33333334 = coord(2/6)
    Abstract
    Wie können begriffliche Strukturen an Topic Maps angebunden werden? Allgemeiner. Wie kann die Wissensorganisation dazu beitragen, dass im Semantic Web eine begriffsbasierte Infrastruktur verfügbar ist? Dieser Frage hat sich die Wissensorganisation bislang noch nicht wirklich angenommen. Insgesamt ist die Berührung zwischen semantischen Wissenstechnologien und wissensorganisatorischen Fragestellungen noch sehr gering, obwohl Begriffsstrukturen, Ontologien und Topic Maps grundsätzlich gut zusammenpassen und ihre gemeinsame Betrachtung Erkenntnisse für zentrale wissensorganisatorische Fragestellungen wie z.B. semantische Interoperabilität und semantisches Retrieval erwarten lässt. Daher motiviert und skizziert dieser Beitrag die Grundidee, nach der es möglich sein müsste, eine Sprache zur Darstellung von Begriffsstrukturen in der Wissensorganisation geeignet mit Topic Maps zu verbinden. Eine genauere Untersuchung und Implementation stehen allerdings weiterhin aus. Speziell wird vermutet, dass sich der Concepto zugrunde liegende Formalismus CLF (Concept Language Formalism) mit Topic Maps vorteilhaft abbilden lässt 3 Damit können Begriffs- und Themennetze realisiert werden, die auf expliziten Begriffssystemen beruhen. Seitens der Wissensorganisation besteht die Notwendigkeit, sich mit aktuellen Entwicklungen auf dem Gebiet des Semantic Web und ontology engineering vertraut zu machen, aber auch die eigene Kompetenz stärker aktiv in diese Gebiete einzubringen. Damit dies geschehen kann, führt dieser Beitrag zum besseren Verständnis zunächst aus Sicht der Wissensorganisation knapp in Ontologien und Topic Maps ein und diskutiert wichtige Überschneidungsbereiche.
    Series
    Fortschritte in der Wissensorganisation; Bd.7
    Source
    Wissensorganisation und Edutainment: Wissen im Spannungsfeld von Gesellschaft, Gestaltung und Industrie. Proceedings der 7. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Berlin, 21.-23.3.2001. Hrsg.: C. Lehner, H.P. Ohly u. G. Rahmstorf
  2. Gödert, W.: Semantische Wissensrepräsentation und Interoperabilität : Teil 2: Ein formales Modell semantischer Interoperabilität (2010) 0.02 
    0.016507369 = product of:
  0.049522102 = sum of:
    0.0071393843 = weight(_text_:in in 1530) [ClassicSimilarity], result of:
      0.0071393843 = score(doc=1530,freq=2.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.120230645 = fieldWeight in 1530, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0625 = fieldNorm(doc=1530)
    0.042382717 = weight(_text_:und in 1530) [ClassicSimilarity], result of:
      0.042382717 = score(doc=1530,freq=10.0), product of:
        0.09675359 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.043654136 = queryNorm
        0.438048 = fieldWeight in 1530, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0625 = fieldNorm(doc=1530)
  0.33333334 = coord(2/6)
    Abstract
    In diesem zweiten Teil wird ein formales Modell zur semantischen Interoperabilität als Brücke zwischen formaler Modellierung und intellektueller Interpretation vorgestellt, das ein besseres Verständnis der zentralen Begriffe von semantischer Ähnlichkeit und Verschiedenheit von Begriffen und Klassen, sowohl als elementare Inhaltsentitäten von Dokumentationssprachen als auch als synthetische Repräsentationen von Dokumentinhalten, ermöglichen soll.
    Source
    Information - Wissenschaft und Praxis. 61(2010) H.1, S.19-28
  3. Gödert, W.: Semantische Wissensrepräsentation und Interoperabilität : Teil 1: Interoperabilität als Weg zur Wissensexploration (2010) 0.02 
    0.015306472 = product of:
  0.045919415 = sum of:
    0.008834538 = weight(_text_:in in 3348) [ClassicSimilarity], result of:
      0.008834538 = score(doc=3348,freq=4.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.14877784 = fieldWeight in 3348, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3348)
    0.037084877 = weight(_text_:und in 3348) [ClassicSimilarity], result of:
      0.037084877 = score(doc=3348,freq=10.0), product of:
        0.09675359 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.043654136 = queryNorm
        0.38329202 = fieldWeight in 3348, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3348)
  0.33333334 = coord(2/6)
    Abstract
    Dieser aus zwei Teilen bestehende Beitrag setzt Methoden der semantischen Wissensrepräsentation in Verbindung zur Gestaltung von Retrievalszenarios für begriffliche Recherchen und insbesondere für die Wissensexploration. Ausgehend von heterogenen Erschließungssituationen werden Konzepte vorgestellt, wie durch Maßnahmen zur Herstellung von Interoperabilität ein Beitrag zur Lösung der Heterogenitätssituation geleistet werden soll. Basierend auf einem, im zweiten Teil vorgestellten, formalen Modell zum besseren Verständnis von semantischer Interoperabilität, wird ein Vorschlag für ein Gesamtsystem entwickelt, das aus einer Kernontologie und lokalisierten semantischen Netzen mit erweitertem Relationenumfang besteht. Die Möglichkeiten zur Recherche und Exploration in einem solchen Gesamtrahmen werden skizziert.
    Source
    Information - Wissenschaft und Praxis. 61(2010) H.1, S.5-18
  4. Semenova, E.; Stricker, M.: ¬Eine Ontologie der Wissenschaftsdisziplinen : Entwicklung eines Instrumentariums für die Wissenskommunikation (2007) 0.02 
    0.015172194 = product of:
  0.04551658 = sum of:
    0.009977593 = weight(_text_:in in 1889) [ClassicSimilarity], result of:
      0.009977593 = score(doc=1889,freq=10.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.16802745 = fieldWeight in 1889, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1889)
    0.035538986 = weight(_text_:und in 1889) [ClassicSimilarity], result of:
      0.035538986 = score(doc=1889,freq=18.0), product of:
        0.09675359 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.043654136 = queryNorm
        0.3673144 = fieldWeight in 1889, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1889)
  0.33333334 = coord(2/6)
    Abstract
    Interdisziplinarität als Kennzeichen des modernen Wissenschaftslebens setzt in Forschung und Lehre eine effiziente Wissenschaftskommunikation voraus, bei der sich die Partner über eine gemeinsame Sprache verständigen können. Klassifikationen und Thesauri übernehmen dabei eine wichtige Rolle. Zu beobachten ist, dass vorhandene Instrumente in ihrem Gefüge zu inflexibel sind, um die komplex ineinander verwobenen Felder der Wissenschaft in ihrer dynamischen Entwicklung adäquat abzubilden, zur (Selbst-)Verständigung über das Wesen und Struktur der Wissenschaftslandschaft sowie zum erfolgreichen Wissensaustausch beizutragen. Ontologien erschließen neue Wege zur Lösung dieser Aufgaben. In einigen Einzelwissenschaften und Teilgebieten ist diesbezüglich eine rege Tätigkeit zu beobachten, es fehlt allerdings noch ein fachübergreifendes Instrumentarium. Im Vortrag wird das von der DFG geförderte Projekt "Entwicklung einer Ontologie der Wissenschaftsdisziplinen" vorgestellt. Es gilt, die oben beschriebene Lücke zu schließen und eine umfassende Ontologie für Erschließung, Recherche und Datenaustausch bei der Wissenschaftskommunikation zu erstellen. Diese Ontologie soll dazu beitragen, eine effiziente Wissenskommunikation, besonders bei interdisziplinären Projekten, zu unterstützen, verfügbare Ressourcen auffindbar zu machen und mögliche Knotenstellen künftiger Kooperationen zu verdeutlichen. Ausgehend von der Kritik an vorhandenen Instrumenten wird derzeit ein Begriffsmodell für die Beschreibung von Wissenschaftsdisziplinen, ihrer zentralen Facetten sowie ihrer interdisziplinären Beziehungen untereinander entwickelt. Das Modell, inspiriert vom Topic Maps Paradigma, basiert auf einer überschaubaren Menge zentraler Konzepte sowie prinzipiell inverser Beziehungen. Eine entsprechende Ontologie wird in unterschiedlichen (technischen) Beschreibungsformaten formuliert werden können. Dies bildet den Grundstein für den Fokus des Projekts, flexible, verteilte, benutzer- wie pflegefreundliche technische Umsetzungen zu entwickeln und mit Kooperationspartnern zu implementieren.
    Source
    Wissenschaftskommunikation der Zukunft (WissKom 2007) : 4. Konferenz der Zentralbibliothek Forschungszentrum Jülich : 6. - 8. November 2007 ; Beiträge und Poster / [WissKom 2007]. Forschungszentrum Jülich GmbH, Zentralbibliothek. Rafael Ball (Hrsg.). [Mit einem Festvortrag von Ernst Pöppel]
  5. Ehrig, M.; Studer, R.: Wissensvernetzung durch Ontologien (2006) 0.01 
    0.013036655 = product of:
  0.039109964 = sum of:
    0.012620768 = weight(_text_:in in 5901) [ClassicSimilarity], result of:
      0.012620768 = score(doc=5901,freq=16.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.21253976 = fieldWeight in 5901, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5901)
    0.026489196 = weight(_text_:und in 5901) [ClassicSimilarity], result of:
      0.026489196 = score(doc=5901,freq=10.0), product of:
        0.09675359 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.043654136 = queryNorm
        0.27378 = fieldWeight in 5901, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5901)
  0.33333334 = coord(2/6)
    Abstract
    In der Informatik sind Ontologien formale Modelle eines Anwendungsbereiches, die die Kommunikation zwischen menschlichen und/oder maschinellen Akteuren unterstützen und damit den Austausch und das Teilen von Wissen in Unternehmen erleichtern. Ontologien zur strukturierten Darstellung von Wissen zu nutzen hat deshalb in den letzten Jahren zunehmende Verbreitung gefunden. Schon heute existieren weltweit tausende Ontologien. Um Interoperabilität zwischen darauf aufbauenden Softwareagenten oder Webservices zu ermöglichen, ist die semantische Integration der Ontologien eine zwingendnotwendige Vorraussetzung. Wie man sieh leicht verdeutlichen kann, ist die rein manuelle Erstellung der Abbildungen ab einer bestimmten Größe. Komplexität und Veränderungsrate der Ontologien nicht mehr ohne weiteres möglich. Automatische oder semiautomatische Technologien müssen den Nutzer darin unterstützen. Das Integrationsproblem beschäftigt Forschung und Industrie schon seit vielen Jahren z. B. im Bereich der Datenbankintegration. Neu ist jedoch die Möglichkeit komplexe semantische Informationen. wie sie in Ontologien vorhanden sind, einzubeziehen. Zur Ontologieintegration wird in diesem Kapitel ein sechsstufiger genereller Prozess basierend auf den semantischen Strukturen eingeführt. Erweiterungen beschäftigen sich mit der Effizienz oder der optimalen Nutzereinbindung in diesen Prozess. Außerdem werden zwei Anwendungen vorgestellt, in denen dieser Prozess erfolgreich umgesetzt wurde. In einem abschließenden Fazit werden neue aktuelle Trends angesprochen. Da die Ansätze prinzipiell auf jedes Schema übertragbar sind, das eine semantische Basis enthält, geht der Einsatzbereich dieser Forschung weit über reine Ontologieanwendungen hinaus.
  6. Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006) 0.01 
    0.00990557 = product of:
  0.02971671 = sum of:
    0.011973113 = weight(_text_:in in 4820) [ClassicSimilarity], result of:
      0.011973113 = score(doc=4820,freq=10.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.20163295 = fieldWeight in 4820, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=4820)
    0.017743597 = product of:
      0.035487194 = sum of:
        0.035487194 = weight(_text_:22 in 4820) [ClassicSimilarity], result of:
          0.035487194 = score(doc=4820,freq=2.0), product of:
            0.15286934 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043654136 = queryNorm
            0.23214069 = fieldWeight in 4820, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=4820)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Abstract
    One of the major problems facing systems for Computer Aided Design (CAD), Architecture Engineering and Construction (AEC) and Geographic Information Systems (GIS) applications today is the lack of interoperability among the various systems. When integrating software applications, substantial di culties can arise in translating information from one application to the other. In this paper, we focus on semantic di culties that arise in software integration. Applications may use di erent terminologies to describe the same domain. Even when appli-cations use the same terminology, they often associate di erent semantics with the terms. This obstructs information exchange among applications. To cir-cumvent this obstacle, we need some way of explicitly specifying the semantics for each terminology in an unambiguous fashion. Ontologies can provide such specification. It will be the task of this paper to explain what ontologies are and how they can be used to facilitate interoperability between software systems used in computer aided design, architecture engineering and construction, and geographic information processing.
    Date
    3.12.2016 18:39:22
  7. Bandholtz, T.; Schulte-Coerne, T.; Glaser, R.; Fock, J.; Keller, T.: iQvoc - open source SKOS(XL) maintenance and publishing tool (2010) 0.01 
    0.0076106074 = product of:
  0.022831822 = sum of:
    0.006246961 = weight(_text_:in in 604) [ClassicSimilarity], result of:
      0.006246961 = score(doc=604,freq=2.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.10520181 = fieldWeight in 604, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0546875 = fieldNorm(doc=604)
    0.01658486 = weight(_text_:und in 604) [ClassicSimilarity], result of:
      0.01658486 = score(doc=604,freq=2.0), product of:
        0.09675359 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.043654136 = queryNorm
        0.17141339 = fieldWeight in 604, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0546875 = fieldNorm(doc=604)
  0.33333334 = coord(2/6)
    Abstract
    iQvoc is a new open source SKOS-XL vocabulary management tool developed by the Federal Environment Agency, Germany, and innoQ Deutschland GmbH. Its immediate purpose is maintaining and publishing reference vocabularies in the upcoming Linked Data cloud of environmental information, but it may be easily adapted to host any SKOS- XL compliant vocabulary. iQvoc is implemented as a Ruby on Rails application running on top of JRuby - the Java implementation of the Ruby Programming Language. To increase the user experience when editing content, iQvoc uses heavily the JavaScript library jQuery.
    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  8. Dobrev, P.; Kalaydjiev, O.; Angelova, G.: From conceptual structures to semantic interoperability of content (2007) 0.01 
    0.007504981 = product of:
  0.022514943 = sum of:
    0.007728611 = weight(_text_:in in 4607) [ClassicSimilarity], result of:
      0.007728611 = score(doc=4607,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1301535 = fieldWeight in 4607, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4607)
    0.014786332 = product of:
      0.029572664 = sum of:
        0.029572664 = weight(_text_:22 in 4607) [ClassicSimilarity], result of:
          0.029572664 = score(doc=4607,freq=2.0), product of:
            0.15286934 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043654136 = queryNorm
            0.19345059 = fieldWeight in 4607, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4607)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Abstract
    Smart applications behave intelligently because they understand at least partially the context where they operate. To do this, they need not only a formal domain model but also formal descriptions of the data they process and their own operational behaviour. Interoperability of smart applications is based on formalised definitions of all their data and processes. This paper studies the semantic interoperability of data in the case of eLearning and describes an experiment and its assessment. New content is imported into a knowledge-based learning environment without real updates of the original domain model, which is encoded as a knowledge base of conceptual graphs. A component called mediator enables the import by assigning dummy metadata annotations for the imported items. However, some functionality of the original system is lost, when processing the imported content, due to the lack of proper metadata annotation which cannot be associated fully automatically. So the paper presents an interoperability scenario when appropriate content items are viewed from the perspective of the original world and can be (partially) reused there.
    Series
    Lecture notes in computer science: Lecture notes in artificial intelligence ; 4604
    Source
    Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a
  9. Widhalm, R.; Mueck, T.A.: Merging topics in well-formed XML topic maps (2003) 0.00 
    0.0025241538 = product of:
  0.015144923 = sum of:
    0.015144923 = weight(_text_:in in 2186) [ClassicSimilarity], result of:
      0.015144923 = score(doc=2186,freq=16.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.25504774 = fieldWeight in 2186, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=2186)
  0.16666667 = coord(1/6)
    Abstract
    Topic Maps are a standardized modelling approach for the semantic annotation and description of WWW resources. They enable an improved search and navigational access on information objects stored in semi-structured information spaces like the WWW. However, the according standards ISO 13250 and XTM (XML Topic Maps) lack formal semantics, several questions concerning e.g. subclassing, inheritance or merging of topics are left open. The proposed TMUML meta model, directly derived from the well known UML meta model, is a meta model for Topic Maps which enables semantic constraints to be formulated in OCL (object constraint language) in order to answer such open questions and overcome possible inconsistencies in Topic Map repositories. We will examine the XTM merging conditions and show, in several examples, how the TMUML meta model enables semantic constraints for Topic Map merging to be formulated in OCL. Finally, we will show how the TM validation process, i.e., checking if a Topic Map is well formed, includes our merging conditions.
    Series
    Lecture notes in computer science; vol. 2870
  10. Koutsomitropoulos, D.A.; Solomou, G.D.; Alexopoulos, A.D.; Papatheodorou, T.S.: Semantic metadata interoperability and inference-based querying in digital repositories (2009) 0.00 
    0.0023611297 = product of:
  0.014166778 = sum of:
    0.014166778 = weight(_text_:in in 3731) [ClassicSimilarity], result of:
      0.014166778 = score(doc=3731,freq=14.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.23857531 = fieldWeight in 3731, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=3731)
  0.16666667 = coord(1/6)
    Abstract
    Metadata applications have evolved in time into highly structured "islands of information" about digital resources, often bearing a strong semantic interpretation. Scarcely however are these semantics being communicated in machine readable and understandable ways. At the same time, the process for transforming the implied metadata knowledge into explicit Semantic Web descriptions can be problematic and is not always evident. In this article we take upon the well-established Dublin Core metadata standard as well as other metadata schemata, which often appear in digital repositories set-ups, and suggest a proper Semantic Web OWL ontology. In this process the authors cope with discrepancies and incompatibilities, indicative of such attempts, in novel ways. Moreover, we show the potential and necessity of this approach by demonstrating inferences on the resulting ontology, instantiated with actual metadata records. The authors conclude by presenting a working prototype that provides for inference-based querying on top of digital repositories.
  11. Boteram, F.; Gödert, W.; Hubrich, J.: Semantic interoperability and retrieval paradigms (2010) 0.00 
    0.0020609628 = product of:
  0.012365777 = sum of:
    0.012365777 = weight(_text_:in in 3362) [ClassicSimilarity], result of:
      0.012365777 = score(doc=3362,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.2082456 = fieldWeight in 3362, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0625 = fieldNorm(doc=3362)
  0.16666667 = coord(1/6)
    Abstract
    This paper presents a new approach to understanding how indexing strategies, models for interoperability and retrieval paradigms interact in information systems and how this can be used to support the design and implementation of components of a semantic navigation for information retrieval systems.
    Series
    Advances in knowledge organization; vol.12
    Source
    Paradigms and conceptual systems in knowledge organization: Proceedings of the Eleventh International ISKO Conference, 23-26 February 2010 Rome, Italy. Edited by Claudio Gnoli and Fulvio Mazzocchi
  12. Burstein, M.; McDermott, D.V.: Ontology translation for interoperability among Semantic Web services (2005) 0.00 
    0.001821651 = product of:
  0.010929906 = sum of:
    0.010929906 = weight(_text_:in in 2661) [ClassicSimilarity], result of:
      0.010929906 = score(doc=2661,freq=12.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.18406484 = fieldWeight in 2661, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2661)
  0.16666667 = coord(1/6)
    Abstract
    Research on semantic web services promises greater interoperability among software agents and web services by enabling content-based automated service discovery and interaction and by utilizing. Although this is to be based on use of shared ontologies published on the semantic web, services produced and described by different developers may well use different, perhaps partly overlapping, sets of ontologies. Interoperability will depend on ontology mappings and architectures supporting the associated translation processes. The question we ask is, does the traditional approach of introducing mediator agents to translate messages between requestors and services work in such an open environment? This article reviews some of the processing assumptions that were made in the development of the semantic web service modeling ontology OWL-S and argues that, as a practical matter, the translation function cannot always be isolated in mediators. Ontology mappings need to be published on the semantic web just as ontologies themselves are. The translation for service discovery, service process model interpretation, task negotiation, service invocation, and response interpretation may then be distributed to various places in the architecture so that translation can be done in the specific goal-oriented informational contexts of the agents performing these processes. We present arguments for assigning translation responsibility to particular agents in the cases of service invocation, response translation, and match- making.
  13. Bean, C.A.: Hierarchical relationships used in mapping between knowledge structures (2006) 0.00 
    0.0018033426 = product of:
  0.010820055 = sum of:
    0.010820055 = weight(_text_:in in 5866) [ClassicSimilarity], result of:
      0.010820055 = score(doc=5866,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1822149 = fieldWeight in 5866, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5866)
  0.16666667 = coord(1/6)
    Abstract
    User-designated Broader-Narrower Term pairs were analyzed to better characterize the nature and structure of the relationships between the pair members, previously determined by experts to be hierarchical in nature. Semantic analysis revealed that almost three-quarters (72%) of the term pairs were characterized as is-a (-kind-of) relationships and the rest (28%) as part-whole relationships. Four basic patterns of syntactic specification were observed. Implications of the findings for mapping strategies are discussed.
    Series
    Advances in knowledge organization; vol.10
  14. Amarger, F.; Chanet, J.-P.; Haemmerlé, O.; Hernandez, N.; Roussey, C.: SKOS sources transformations for ontology engineering : agronomical taxonomy use case (2014) 0.00 
    0.0017848461 = product of:
  0.010709076 = sum of:
    0.010709076 = weight(_text_:in in 1593) [ClassicSimilarity], result of:
      0.010709076 = score(doc=1593,freq=8.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.18034597 = fieldWeight in 1593, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=1593)
  0.16666667 = coord(1/6)
    Abstract
    Sources like thesauri or taxonomies are already used as input in ontology development process. Some of them are also published on the LOD using the SKOS format. Reusing this type of sources to build an ontology is not an easy task. The ontology developer has to face different syntax and different modelling goals. We propose in this paper a new methodology to transform several non-ontological sources into a single ontology. We take into account: the redundancy of the knowledge extracted from sources in order to discover the consensual knowledge and Ontology Design Patterns (ODPs) to guide the transformation process. We have evaluated our methodology by creating an ontology on wheat taxonomy from three sources: Agrovoc thesaurus, TaxRef taxonomy, NCBI taxonomy.
    Series
    Communications in computer and information science; 478
  15. Soergel, D.: Towards a relation ontology for the Semantic Web (2011) 0.00 
    0.0015457221 = product of:
  0.009274333 = sum of:
    0.009274333 = weight(_text_:in in 4342) [ClassicSimilarity], result of:
      0.009274333 = score(doc=4342,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1561842 = fieldWeight in 4342, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=4342)
  0.16666667 = coord(1/6)
    Abstract
    The Semantic Web consists of data structured for use by computer programs, such as data sets made available under the Linked Open Data initiative. Much of this data is structured following the entity-relationship model encoded in RDF for syntactic interoperability. For semantic interoperability, the semantics of the relationships used in any given dataset needs to be made explicit. Ultimately this requires an inventory of these relationships structured around a relation ontology. This talk will outline a blueprint for such an inventory, including a format for the description/definition of binary and n-ary relations, drawing on ideas put forth in the classification and thesaurus community over the last 60 years, upper level ontologies, systems like FrameNet, the Buffalo Relation Ontology, and an analysis of linked data sets.
  16. Khiat, A.; Benaissa, M.: Approach for instance-based ontology alignment : using argument and event structures of generative lexicon (2014) 0.00 
    0.0015457221 = product of:
  0.009274333 = sum of:
    0.009274333 = weight(_text_:in in 1577) [ClassicSimilarity], result of:
      0.009274333 = score(doc=1577,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1561842 = fieldWeight in 1577, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=1577)
  0.16666667 = coord(1/6)
    Abstract
    Ontology alignment became a very important problem to ensure semantic interoperability for different sources of information heterogeneous and distributed. Instance-based ontology alignment represents a very promising technique to find semantic correspondences between entities of different ontologies when they contain a lot of instances. In this paper, we describe a new approach to manage ontologies that do not share common instances.This approach extracts the argument and event structures from a set of instances of the concept of the source ontology and compared them with other semantic features extracted from a set of instances of the concept of the target ontology using Generative Lexicon Theory. We show that it is theoretically powerful because it is based on linguistic semantics and useful in practice. We present the experimental results obtained by running our approach on Biblio test of Benchmark series of OAEI 2011. The results show the good performance of our approach.
    Series
    Communications in computer and information science; 478
  17. Rocha Souza, R.; Lemos, D.: a comparative analysis : Knowledge organization systems for the representation of multimedia resources on the Web (2020) 0.00 
    0.0015457221 = product of:
  0.009274333 = sum of:
    0.009274333 = weight(_text_:in in 5993) [ClassicSimilarity], result of:
      0.009274333 = score(doc=5993,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1561842 = fieldWeight in 5993, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=5993)
  0.16666667 = coord(1/6)
    Abstract
    The lack of standardization in the production, organization and dissemination of information in documentation centers and institutions alike, as a result from the digitization of collections and their availability on the internet has called for integration efforts. The sheer availability of multimedia content has fostered the development of many distinct and, most of the time, independent metadata standards for its description. This study aims at presenting and comparing the existing standards of metadata, vocabularies and ontologies for multimedia annotation and also tries to offer a synthetic overview of its main strengths and weaknesses, aiding efforts for semantic integration and enhancing the findability of available multimedia resources on the web. We also aim at unveiling the characteristics that could, should and are perhaps not being highlighted in the characterization of multimedia resources.
  18. Balakrishnan, U,; Soergel, D.; Helfer, O.: Representing concepts through description logic expressions for knowledge organization system (KOS) mapping (2020) 0.00 
    0.0014873719 = product of:
  0.008924231 = sum of:
    0.008924231 = weight(_text_:in in 144) [ClassicSimilarity], result of:
      0.008924231 = score(doc=144,freq=2.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.15028831 = fieldWeight in 144, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.078125 = fieldNorm(doc=144)
  0.16666667 = coord(1/6)
    Series
    Advances in knowledge organization; vol.17
  19. Boteram, F.: "Content architecture" : semantic interoperability in an international comprehensive knowledge organisation system (2010) 0.00 
    0.0013303459 = product of:
  0.007982075 = sum of:
    0.007982075 = weight(_text_:in in 647) [ClassicSimilarity], result of:
      0.007982075 = score(doc=647,freq=10.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.13442196 = fieldWeight in 647, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.03125 = fieldNorm(doc=647)
  0.16666667 = coord(1/6)
    Abstract
    Purpose - This paper seeks to develop a specified typology of various levels of semantic interoperability, designed to provide semantically expressive and functional means to interconnect typologically different sub-systems in an international comprehensive knowledge organization system, supporting advanced information retrieval and exploration strategies. Design/methodology/approach - Taking the analysis of rudimentary forms of a functional interoperability based on simple pattern matching as a starting-point, more refined strategies to provide semantic interoperability, which is actually reaching the conceptual and even thematic level, are being developed. The paper also examines the potential benefits and perspectives of the selective transfer of modelling strategies from the field of semantic technologies for the refinement of relational structures of inter-system and inter-concept relations as a requirement for expressive and functional indexing languages supporting advanced types of semantic interoperability. Findings - As the principles and strategies of advanced information retrieval systems largely depend on semantic information, new concepts and strategies to achieve semantic interoperability have to be developed. Research limitations/implications - The approach has been developed in the functional and structural context of an international comprehensive system integrating several heterogeneous knowledge organization systems and indexing languages by interconnecting them to a central conceptual structure operating as a spine in an overall system designed to support retrieval and exploration of bibliographic records representing complex conceptual entities. Originality/value - Research and development aimed at providing technical and structural interoperability has to be complemented by a thorough and precise reflection and definition of various degrees and types of interoperability on the semantic level as well. The approach specifies these levels and reflects the implications and their potential for advanced strategies of retrieval and exploration.
    Footnote
    Beitrag in einem Special Issue: Content architecture: exploiting and managing diverse resources: proceedings of the first national conference of the United Kingdom chapter of the International Society for Knowedge Organization (ISKO).
  20. Vlachidis, A.; Tudhope, D.: ¬A knowledge-based approach to information extraction for semantic interoperability in the archaeology domain (2016) 0.00 
    0.0012881019 = product of:
  0.007728611 = sum of:
    0.007728611 = weight(_text_:in in 2895) [ClassicSimilarity], result of:
      0.007728611 = score(doc=2895,freq=6.0), product of:
        0.059380736 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.043654136 = queryNorm
        0.1301535 = fieldWeight in 2895, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2895)
  0.16666667 = coord(1/6)
    Abstract
    The article presents a method for automatic semantic indexing of archaeological grey-literature reports using empirical (rule-based) Information Extraction techniques in combination with domain-specific knowledge organization systems. The semantic annotation system (OPTIMA) performs the tasks of Named Entity Recognition, Relation Extraction, Negation Detection, and Word-Sense Disambiguation using hand-crafted rules and terminological resources for associating contextual abstractions with classes of the standard ontology CIDOC Conceptual Reference Model (CRM) for cultural heritage and its archaeological extension, CRM-EH. Relation Extraction (RE) performance benefits from a syntactic-based definition of RE patterns derived from domain oriented corpus analysis. The evaluation also shows clear benefit in the use of assistive natural language processing (NLP) modules relating to Word-Sense Disambiguation, Negation Detection, and Noun Phrase Validation, together with controlled thesaurus expansion. The semantic indexing results demonstrate the capacity of rule-based Information Extraction techniques to deliver interoperable semantic abstractions (semantic annotations) with respect to the CIDOC CRM and archaeological thesauri. Major contributions include recognition of relevant entities using shallow parsing NLP techniques driven by a complimentary use of ontological and terminological domain resources and empirical derivation of context-driven RE rules for the recognition of semantic relationships from phrases of unstructured text.

Authors

Years

Languages

  • e 17
  • d 6

Themes