Search (42 results, page 2 of 3)

  • × theme_ss:"Semantic Web"
  • × year_i:[2000 TO 2010}
  1. Wang, H.; Liu, Q.; Penin, T.; Fu, L.; Zhang, L.; Tran, T.; Yu, Y.; Pan, Y.: Semplore: a scalable IR approach to search the Web of Data (2009) 0.01
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    Source
    Web semantics: science, services and agents on the World Wide Web. 7(2009) no.3, S.177-188
  2. Macgregor, G.: Introduction to a special issue on digital libraries and the semantic web : context, applications and research (2008) 0.01
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    Date
    7. 6.2008 18:36:17
  3. Joint, N.: ¬The practitioner librarian and the semantic web : ANTAEUS (2008) 0.01
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    Date
    7. 6.2008 18:35:50
  4. Studer, R.; Studer, H.-P.; Studer, A.: Semantisches Knowledge Retrieval (2001) 0.01
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    Content
    Inhalt: 1. Einführung - 2. Wissensmanagement - 3. Information Retrieval - 3.1. Methoden und Techniken - 3.2. Information Retrieval in der Anwendung - 4. Semantische Ansätze - 4.1. Wissen modellieren - Ontologie - 4.2. Neues Wissen inferieren - 5. Knowledge Retrieval in der Anwendung - 6. Zukunftsaussichten - 7. Fazit
  5. Hüsken, P.: Informationssuche im Semantic Web : Methoden des Information Retrieval für die Wissensrepräsentation (2006) 0.01
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    Isbn
    978-3-86550-886-7
  6. ¬The Semantic Web : research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings (2005) 0.01
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    Isbn
    978-3-540-26124-7
  7. Veltman, K.H.: Syntactic and semantic interoperability : new approaches to knowledge and the Semantic Web (2001) 0.01
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    Abstract
    At VVWW-7 (Brisbane, 1997), Tim Berners-Lee outlined his vision of a global reasoning web. At VVWW- 8 (Toronto, May 1998), he developed this into a vision of a semantic web, where one Gould search not just for isolated words, but for meaning in the form of logically provable claims. In the past four years this vision has spread with amazing speed. The semantic web has been adopted by the European Commission as one of the important goals of the Sixth Framework Programme. In the United States it has become linked with the Defense Advanced Research Projects Agency (DARPA). While this quest to achieve a semantic web is new, the quest for meaning in language has a history that is almost as old as language itself. Accordingly this paper opens with a survey of the historical background. The contributions of the Dublin Core are reviewed briefly. To achieve a semantic web requires both syntactic and semantic interoperability. These challenges are outlined. A basic contention of this paper is that semantic interoperability requires much more than a simple agreement concerning the static meaning of a term. Different levels of agreement (local, regional, national and international) are involved and these levels have their own history. Hence, one of the larger challenges is to create new systems of knowledge organization, which identify and connect these different levels. With respect to meaning or semantics, early twentieth century pioneers such as Wüster were hopeful that it might be sufficient to limit oneself to isolated terms and words without reference to the larger grammatical context: to concept systems rather than to propositional logic. While a fascination with concept systems implicitly dominates many contemporary discussions, this paper suggests why this approach is not sufficient. The final section of this paper explores how an approach using propositional logic could lead to a new approach to universals and particulars. This points to a re-organization of knowledge, and opens the way for a vision of a semantic web with all the historical and cultural richness and complexity of language itself.
    Source
    New review of information networking. 7(2001) no.xx, S.xx-xx
  8. Bizer, C.; Lehmann, J.; Kobilarov, G.; Auer, S.; Becker, C.; Cyganiak, R.; Hellmann, S.: DBpedia: a crystallization point for the Web of Data. (2009) 0.01
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    Source
    Journal of Web semantics: science, services and agents on the World Wide Web, no.7, S.154-165
  9. Prasad, A.R.D.; Madalli, D.P.: Faceted infrastructure for semantic digital libraries (2008) 0.01
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    Date
    7. 6.2008 18:47:03
  10. Sini, M.; Lauser, B.; Salokhe, G.; Keizer, J.; Katz, S.: ¬The AGROVOC concept server : rationale, goals and usage (2008) 0.01
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    Date
    7. 6.2008 18:42:15
  11. Krause, J.: Semantic heterogeneity : comparing new semantic web approaches with those of digital libraries (2008) 0.01
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    Date
    7. 6.2008 18:49:12
  12. Mayr, P.; Mutschke, P.; Petras, V.: Reducing semantic complexity in distributed digital libraries : Treatment of term vagueness and document re-ranking (2008) 0.01
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    Date
    7. 6.2008 18:47:24
  13. Handbook on ontologies (2004) 0.01
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    Isbn
    3-540-40834-7
  14. Isaac, A.: Aligning thesauri for an integrated access to Cultural Heritage Resources (2007) 0.01
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    Abstract
    Currently, a number of efforts are being carried out to integrate collections from different institutions and containing heterogeneous material. Examples of such projects are The European Library [1] and the Memory of the Netherlands [2]. A crucial point for the success of these is the availability to provide a unified access on top of the different collections, e.g. using one single vocabulary for querying or browsing the objects they contain. This is made difficult by the fact that the objects from different collections are often described using different vocabularies - thesauri, classification schemes - and are therefore not interoperable at the semantic level. To solve this problem, one can turn to semantic links - mappings - between the elements of the different vocabularies. If one knows that a concept C from a vocabulary V is semantically equivalent to a concept to a concept D from vocabulary W, then an appropriate search engine can return all the objects that were indexed against D for a query for objects described using C. We thus have an access to other collections, using a single one vocabulary. This is however an ideal situation, and hard alignment work is required to reach it. Several projects in the past have tried to implement such a solution, like MACS [3] and Renardus [4]. They have demonstrated very interesting results, but also highlighted the difficulty of aligning manually all the different vocabularies involved in practical cases, which sometimes contain hundreds of thousands of concepts. To alleviate this problem, a number of tools have been proposed in order to provide with candidate mappings between two input vocabularies, making alignment a (semi-) automatic task. Recently, the Semantic Web community has produced a lot of these alignment tools'. Several techniques are found, depending on the material they exploit: labels of concepts, structure of vocabularies, collection objects and external knowledge sources. Throughout our presentation, we will present a concrete heterogeneity case where alignment techniques have been applied to build a (pilot) browser, developed in the context of the STITCH project [5]. This browser enables a unified access to two collections of illuminated manuscripts, using the description vocabulary used in the first collection, Mandragore [6], or the one used by the second, Iconclass [7]. In our talk, we will also make the point for using unified representations the vocabulary semantic and lexical information. Additionally to ease the use of the alignment tools that have these vocabularies as input, turning to a standard representation format helps designing applications that are more generic, like the browser we demonstrate. We give pointers to SKOS [8], an open and web-enabled format currently developed by the Semantic Web community.
    References [1] http:// www.theeuropeanlibrary.org [2] http://www.geheugenvannederland.nl [3] http://macs.cenl.org [4] Day, M., Koch, T., Neuroth, H.: Searching and browsing multiple subject gateways in the Renardus service. In Proceedings of the RC33 Sixth International Conference on Social Science Methodology, Amsterdam , 2005. [5] http://stitch.cs.vu.nl [6] http://mandragore.bnf.fr [7] http://www.iconclass.nl [8] www.w3.org/2004/02/skos/ 1 The Semantic Web vision supposes sharing data using different conceptualizations (ontologies), and therefore implies to tackle the semantic interoperability problem
  15. Daconta, M.C.; Oberst, L.J.; Smith, K.T.: ¬The Semantic Web : A guide to the future of XML, Web services and knowledge management (2003) 0.01
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    Date
    22. 5.2007 10:37:38
  16. Subirats, I.; Prasad, A.R.D.; Keizer, J.; Bagdanov, A.: Implementation of rich metadata formats and demantic tools using DSpace (2008) 0.01
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    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  17. Shoffner, M.; Greenberg, J.; Kramer-Duffield, J.; Woodbury, D.: Web 2.0 semantic systems : collaborative learning in science (2008) 0.01
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    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  18. Botana Varela, J.: Unscharfe Wissensrepräsentationen bei der Implementation des Semantic Web (2004) 0.01
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    Abstract
    In der vorliegenden Arbeit soll einen Ansatz zur Implementation einer Wissensrepräsentation mit den in Abschnitt 1.1. skizzierten Eigenschaften und dem Semantic Web als Anwendungsbereich vorgestellt werden. Die Arbeit ist im Wesentlichen in zwei Bereiche gegliedert: dem Untersuchungsbereich (Kapitel 2-5), in dem ich die in Abschnitt 1.1. eingeführte Terminologie definiert und ein umfassender Überblick über die zugrundeliegenden Konzepte gegeben werden soll, und dem Implementationsbereich (Kapitel 6), in dem aufbauend auf dem im Untersuchungsbereich erarbeiteten Wissen einen semantischen Suchdienst entwickeln werden soll. In Kapitel 2 soll zunächst das Konzept der semantischen Interpretation erläutert und in diesem Kontext hauptsächlich zwischen Daten, Information und Wissen unterschieden werden. In Kapitel 3 soll Wissensrepräsentation aus einer kognitiven Perspektive betrachtet und in diesem Zusammenhang das Konzept der Unschärfe beschrieben werden. In Kapitel 4 sollen sowohl aus historischer als auch aktueller Sicht die Ansätze zur Wissensrepräsentation und -auffindung beschrieben und in diesem Zusammenhang das Konzept der Unschärfe diskutiert werden. In Kapitel 5 sollen die aktuell im WWW eingesetzten Modelle und deren Einschränkungen erläutert werden. Anschließend sollen im Kontext der Entscheidungsfindung die Anforderungen beschrieben werden, die das WWW an eine adäquate Wissensrepräsentation stellt, und anhand der Technologien des Semantic Web die Repräsentationsparadigmen erläutert werden, die diese Anforderungen erfüllen. Schließlich soll das Topic Map-Paradigma erläutert werden. In Kapitel 6 soll aufbauend auf die im Untersuchtungsbereich gewonnenen Erkenntnisse ein Prototyp entwickelt werden. Dieser besteht im Wesentlichen aus Softwarewerkzeugen, die das automatisierte und computergestützte Extrahieren von Informationen, das unscharfe Modellieren, sowie das Auffinden von Wissen unterstützen. Die Implementation der Werkzeuge erfolgt in der Programmiersprache Java, und zur unscharfen Wissensrepräsentation werden Topic Maps eingesetzt. Die Implementation wird dabei schrittweise vorgestellt. Schließlich soll der Prototyp evaluiert und ein Ausblick auf zukünftige Erweiterungsmöglichkeiten gegeben werden. Und schließlich soll in Kapitel 7 eine Synthese formuliert werden.
  19. Shaw, R.; Buckland, M.: Open identification and linking of the four Ws (2008) 0.00
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    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  20. Towards the Semantic Web : ontology-driven knowledge management (2004) 0.00
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    Isbn
    0-470-84867-7

Languages

  • e 33
  • d 9

Types

  • a 23
  • el 10
  • m 7
  • s 4
  • r 2
  • x 2
  • n 1
  • More… Less…