Search (27 results, page 1 of 2)

  • × theme_ss:"Wissensrepräsentation"
  • × type_ss:"el"
  • × year_i:[2010 TO 2020}
  1. Hoppe, T.: Semantische Filterung : ein Werkzeug zur Steigerung der Effizienz im Wissensmanagement (2013) 0.01
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    Abstract
    Dieser Artikel adressiert einen Randbereich des Wissensmanagements: die Schnittstelle zwischen Unternehmens-externen Informationen im Internet und den Leistungsprozessen eines Unternehmens. Diese Schnittstelle ist besonders für Unternehmen von Interesse, deren Leistungsprozesse von externen Informationen abhängen und die auf diese Prozesse angewiesen sind. Wir zeigen an zwei Fallbeispielen, dass die inhaltliche Filterung von Informationen beim Eintritt ins Unternehmen ein wichtiges Werkzeug darstellt, um daran anschließende Wissens- und Informationsmanagementprozesse effizient zu gestalten.
    Date
    29. 9.2015 18:56:44
    Source
    Open journal of knowledge management. 2013, Ausgabe VII = http://www.community-of-knowledge.de/beitrag/semantische-filterung-ein-werkzeug-zur-steigerung-der-effizienz-im-wissensmanagement/
  2. Haenelt, K.: Semantik im Wiki : am Beispiel des MediaWiki und Semantic MediaWiki (2011) 0.00
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  3. Bauckhage, C.: Moderne Textanalyse : neues Wissen für intelligente Lösungen (2016) 0.00
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    Abstract
    Im Zuge der immer größeren Verfügbarkeit von Daten (Big Data) und rasanter Fortschritte im Daten-basierten maschinellen Lernen haben wir in den letzten Jahren Durchbrüche in der künstlichen Intelligenz erlebt. Dieser Vortrag beleuchtet diese Entwicklungen insbesondere im Hinblick auf die automatische Analyse von Textdaten. Anhand einfacher Beispiele illustrieren wir, wie moderne Textanalyse abläuft und zeigen wiederum anhand von Beispielen, welche praktischen Anwendungsmöglichkeiten sich heutzutage in Branchen wie dem Verlagswesen, der Finanzindustrie oder dem Consulting ergeben.
  4. Stock, W.G.: Wissensrepräsentation (2010) 0.00
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    Source
    http://www.phil-fak.uni-duesseldorf.de/fileadmin/Redaktion/Institute/Informationswissenschaft/volkmar/1238412202wissensrep.pdf
  5. Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017) 0.00
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    Abstract
    Diese Publikation beschreibt die Zusammenhänge zwischen wissenshaltigen begriffsorientierten Terminologien, Ontologien, Big Data und künstliche Intelligenz.
    Date
    13.12.2017 14:17:22
  6. Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.00
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    Date
    29. 7.2011 14:44:56
    26.12.2011 13:40:22
  7. Miller, S.: Introduction to ontology concepts and terminology : DC-2013 Tutorial, September 2, 2013. (2013) 0.00
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    Content
    Tutorial topics and outline 1. Tutorial Background Overview The Semantic Web, Linked Data, and the Resource Description Framework 2. Ontology Basics and RDFS Tutorial Semantic modeling, domain ontologies, and RDF Vocabulary Description Language (RDFS) concepts and terminology Examples: domain ontologies, models, and schemas Exercises 3. OWL Overview Tutorial Web Ontology Language (OWL): selected concepts and terminology Exercises
    Source
    DC-2013: International Conference on Dublin Core and Metadata: Online Proceedings [http://dcevents.dublincore.org/index.php/IntConf/dc-2013/schedConf/presentations]
  8. Assem, M. van; Rijgersberg, H.; Wigham, M.; Top, J.: Converting and annotating quantitative data tables (2010) 0.00
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    Date
    29. 7.2011 14:44:56
    Source
    The Semantic Web - ISWC 2010. 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. Eds.: Peter F. Patel-Schneider et al
  9. Onofri, A.: Concepts in context (2013) 0.00
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    Abstract
    My thesis discusses two related problems that have taken center stage in the recent literature on concepts: 1) What are the individuation conditions of concepts? Under what conditions is a concept Cv(1) the same concept as a concept Cv(2)? 2) What are the possession conditions of concepts? What conditions must be satisfied for a thinker to have a concept C? The thesis defends a novel account of concepts, which I call "pluralist-contextualist": 1) Pluralism: Different concepts have different kinds of individuation and possession conditions: some concepts are individuated more "coarsely", have less demanding possession conditions and are widely shared, while other concepts are individuated more "finely" and not shared. 2) Contextualism: When a speaker ascribes a propositional attitude to a subject S, or uses his ascription to explain/predict S's behavior, the speaker's intentions in the relevant context determine the correct individuation conditions for the concepts involved in his report. In chapters 1-3 I defend a contextualist, non-Millian theory of propositional attitude ascriptions. Then, I show how contextualism can be used to offer a novel perspective on the problem of concept individuation/possession. More specifically, I employ contextualism to provide a new, more effective argument for Fodor's "publicity principle": if contextualism is true, then certain specific concepts must be shared in order for interpersonally applicable psychological generalizations to be possible. In chapters 4-5 I raise a tension between publicity and another widely endorsed principle, the "Fregean constraint" (FC): subjects who are unaware of certain identity facts and find themselves in so-called "Frege cases" must have distinct concepts for the relevant object x. For instance: the ancient astronomers had distinct concepts (HESPERUS/PHOSPHORUS) for the same object (the planet Venus). First, I examine some leading theories of concepts and argue that they cannot meet both of our constraints at the same time. Then, I offer principled reasons to think that no theory can satisfy (FC) while also respecting publicity. (FC) appears to require a form of holism, on which a concept is individuated by its global inferential role in a subject S and can thus only be shared by someone who has exactly the same inferential dispositions as S. This explains the tension between publicity and (FC), since holism is clearly incompatible with concept shareability. To solve the tension, I suggest adopting my pluralist-contextualist proposal: concepts involved in Frege cases are holistically individuated and not public, while other concepts are more coarsely individuated and widely shared; given this "plurality" of concepts, we will then need contextual factors (speakers' intentions) to "select" the specific concepts to be employed in our intentional generalizations in the relevant contexts. In chapter 6 I develop the view further by contrasting it with some rival accounts. First, I examine a very different kind of pluralism about concepts, which has been recently defended by Daniel Weiskopf, and argue that it is insufficiently radical. Then, I consider the inferentialist accounts defended by authors like Peacocke, Rey and Jackson. Such views, I argue, are committed to an implausible picture of reference determination, on which our inferential dispositions fix the reference of our concepts: this leads to wrong predictions in all those cases of scientific disagreement where two parties have very different inferential dispositions and yet seem to refer to the same natural kind.
    Content
    Vgl.: http://hdl.handle.net/10023/3462. - Steht nicht im Volltext zur Verfügung.
  10. Assem, M. van: Converting and integrating vocabularies for the Semantic Web (2010) 0.00
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    Date
    29. 7.2011 14:44:56
    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  11. Hunger, M.; Neubauer, P.: ¬Die vernetzte Welt : Abfragesprachen für Graphendatenbanken (2013) 0.00
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    Abstract
    Graphendatenbanken sind darauf optimiert, stark miteinander vernetzte Informationen effizient zu speichern und greifbar zu machen. Welchen Ansprüchen müssen Abfragesprachen genügen, damit sie für die Arbeit mit diesen Datenbanken geeignet sind? Bei der Aufarbeitung realer Informationen zeigt sich, dass ein hoher, aber unterschätzter Wert in den Beziehungen zwischen Elementen steckt. Seien es Ereignisse aus Geschichte und Politik, Personen in realen und virtuellen sozialen Netzen, Proteine und Gene, Abhängigkeiten in Märkten und Ökonomien oder Rechnernetze, Computer, Software und Anwender - alles ist miteinander verbunden. Der Graph ist ein Datenmodell, das solche Verbindungsgeflechte abbilden kann. Leider lässt sich das Modell mit relationalen und Aggregat-orientierten NoSQL-Datenbanken ab einer gewissen Komplexität jedoch schwer handhaben. Graphendatenbanken sind dagegen darauf optimiert, solche stark miteinander vernetzten Informationen effizient zu speichern und greifbar zu machen. Auch komplexe Fragen lassen sich durch ausgefeilte Abfragen schnell beantworten. Hierbei kommt es auf die geeignete Abfragesprache an.
  12. Borchers, D.: Missing Link : Wenn der Kasten denkt - Niklas Luhmann und die Folgen (2017) 0.00
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    Source
    https://www.heise.de/newsticker/meldung/Missing-Link-Wenn-der-Kasten-denkt-Niklas-Luhmann-und-die-Folgen-3919843.html
  13. Cumyn, M.; Reiner, G.; Mas, S.; Lesieur, D.: Legal knowledge representation using a faceted scheme (2019) 0.00
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    Source
    Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law, ICAIL 2019, Montreal, QC, Canada, June 17-21, 2019 [https://doi.org/10.1145/3322640.3326735]
  14. Blanco, E.; Cankaya, H.C.; Moldovan, D.: Composition of semantic relations : model and applications (2010) 0.00
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    Source
    Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), Poster Volume, Beijing, China. Ed.: Chu-Ren Huang and Dan Jurafsky
  15. Bandholtz, T.; Schulte-Coerne, T.; Glaser, R.; Fock, J.; Keller, T.: iQvoc - open source SKOS(XL) maintenance and publishing tool (2010) 0.00
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    Theme
    Konzeption und Anwendung des Prinzips Thesaurus
  16. Halpin, H.; Hayes, P.J.; McCusker, J.P.; McGuinness, D.L.; Thompson, H.S.: When owl:sameAs isn't the same : an analysis of identity in linked data (2010) 0.00
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    Source
    The Semantic Web - ISWC 2010. 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. Eds.: Peter F. Patel-Schneider et al
  17. Blanco, E.; Moldovan, D.: ¬A model for composing semantic relations (2011) 0.00
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    Source
    Proceedings of the 9th International Conference on Computational Semantics (IWCS 2011), Oxford, UK. Eds.: Johan Bos and Stephen Pulman
  18. Bold, N.; Kim, W.-J.; Yang, J.-D.: Converting object-based thesauri into XML Topic Maps (2010) 0.00
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    Source
    2010 2nd International Conference on Education Technology and Computer (ICETC)
  19. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.00
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    Date
    16.11.2018 14:22:01
  20. Gómez-Pérez, A.; Corcho, O.: Ontology languages for the Semantic Web (2015) 0.00
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    Abstract
    Ontologies have proven to be an essential element in many applications. They are used in agent systems, knowledge management systems, and e-commerce platforms. They can also generate natural language, integrate intelligent information, provide semantic-based access to the Internet, and extract information from texts in addition to being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web-known as the Semantic Web-which has been defined as "the conceptual structuring of the Web in an explicit machine-readable way."1 This definition does not differ too much from the one used for defining an ontology: "An ontology is an explicit, machinereadable specification of a shared conceptualization."2 In fact, new ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires-solving the heterogeneous data exchange in this heterogeneous environment. Here, we don't decide which language is best of the Semantic Web. Rather, our goal is to help developers find the most suitable language for their representation needs. The authors analyze the most representative ontology languages created for the Web and compare them using a common framework.
    Content
    Vgl.: http://oa.upm.es/2646/1/JCR01.pdf.