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  1. Bender, B.: Digitale Mündigkeit? : Definition und Dimensionen: eine theoretische Fundierung zwischen Medienbildung und Medienkompetenz (2016) 0.00 
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    Pages
    IV, 101 S
  2. Zudnik, J.: Artifizielle Semantik : Wider das Chinesische Zimmer (2017) 0.00 
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    Pages
    57 S
  3. Castellanos Ardila, J.P.: Investigation of an OSLC-domain targeting ISO 26262 : focus on the left side of the software V-model (2016) 0.00 
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    Pages
    92 S
  4. Sebastian, Y.: Literature-based discovery by learning heterogeneous bibliographic information networks (2017) 0.00 
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    Pages
    xix, 215 S
  5. Bredack, J.: Terminologieextraktion von Mehrwortgruppen in kunsthistorischen Fachtexten (2013) 0.00 
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    Pages
    VI, 66 S
  6. Ammann, A.: Klassifikation dynamischer Wissensräume : multifaktorielle Wechselbeziehungen zur Generierung und Gestaltung konstellativer dynamischer und mehrdimensionaler Wissensräume mit einem Fokus der Anwendung in der Zahn-, Mund- und Kieferheilkunde am Beispiel der enossalen Implantologie (2012) 0.00 
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    172 S
  7. Karlova-Bourbonus, N.: Automatic detection of contradictions in texts (2018) 0.00 
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    258 S
  8. Hannech, A.: Système de recherche d'information étendue basé sur une projection multi-espaces (2018) 0.00 
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    Abstract
    Since its appearance in the early 90's, the World Wide Web (WWW or Web) has provided universal access to knowledge and the world of information has been primarily witness to a great revolution (the digital revolution). It quickly became very popular, making it the largest and most comprehensive database and knowledge base thanks to the amount and diversity of data it contains. However, the considerable increase and evolution of these data raises important problems for users, in particular for accessing the documents most relevant to their search queries. In order to cope with this exponential explosion of data volume and facilitate their access by users, various models are offered by information retrieval systems (IRS) for the representation and retrieval of web documents. Traditional SRIs use simple keywords that are not semantically linked to index and retrieve these documents. This creates limitations in terms of the relevance and ease of exploration of results. To overcome these limitations, existing techniques enrich documents by integrating external keywords from different sources. However, these systems still suffer from limitations that are related to the exploitation techniques of these sources of enrichment. When the different sources are used so that they cannot be distinguished by the system, this limits the flexibility of the exploration models that can be applied to the results returned by this system. Users then feel lost to these results, and find themselves forced to filter them manually to select the relevant information. If they want to go further, they must reformulate and target their search queries even more until they reach the documents that best meet their expectations. In this way, even if the systems manage to find more relevant results, their presentation remains problematic. In order to target research to more user-specific information needs and improve the relevance and exploration of its research findings, advanced SRIs adopt different data personalization techniques that assume that current research of user is directly related to his profile and / or previous browsing / search experiences.
    Pages
    351 S
  9. Vocht, L. De: Exploring semantic relationships in the Web of Data : Semantische relaties verkennen in data op het web (2017) 0.00 
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    Pages
    XXV, 184 S

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