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  • × theme_ss:"Wissensrepräsentation"
  1. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.04 
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  2. Iosif, V.; Mika, P.; Larsson, R.; Akkermans, H.: Field experimenting with Semantic Web tools in a virtual organization (2004) 0.03 
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    Abstract
    How do we test Semantic Web tools? How can we know that they perform better than current technologies for knowledge management? What does 'better' precisely mean? How can we operationalize and measure this? Some of these questions may be partially answered by simulations in lab experiments that for example look at the speed or scalability of algorithms. However, it is not clear in advance to what extent such laboratory results carry over to the real world. Quality is in the eye of the beholder, and so the quality of Semantic Web methods will very much depend on the perception of their usefulness as seen by tool users. This can only be tested by carefully designed field experiments. In this chapter, we discuss the design considerations and set-up of field experiments with Semantic Web tools, and illustrate these with case examples from a virtual organization in industrial research.
  3. Kavouras, M.; Kokla, M.: Theories of geographic concepts : ontological approaches to semantic integration (2008) 0.03 
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    LCSH
    Geographical perception
    Subject
    Geographical perception
  4. Kless, D.; Milton, S.; Kazmierczak, E.; Lindenthal, J.: Thesaurus and ontology structure : formal and pragmatic differences and similarities (2015) 0.03 
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    Abstract
    Thesauri and other types of controlled vocabularies are increasingly re-engineered into ontologies described using the Web Ontology Language (OWL), particularly in the life sciences. This has led to the perception by some that thesauri are ontologies once they are described by using the syntax of OWL while others have emphasized the need to re-engineer a vocabulary to use it as ontology. This confusion is rooted in different perceptions of what ontologies are and how they differ from other types of vocabularies. In this article, we rigorously examine the structural differences and similarities between thesauri and meaning-defining ontologies described in OWL. Specifically, we conduct (a) a conceptual comparison of thesauri and ontologies, and (b) a comparison of a specific thesaurus and a specific ontology in the same subject field. Our results show that thesauri and ontologies need to be treated as 2 orthogonal kinds of models with superficially similar structures. An ontology is not a good thesaurus, nor is a thesaurus a good ontology. A thesaurus requires significant structural and other content changes to become an ontology, and vice versa.
  5. Amirhosseini, M.: Theoretical base of quantitative evaluation of unity in a thesaurus term network based on Kant's epistemology (2010) 0.03 
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    Abstract
    The quantitative evaluation of thesauri has been carried out much further since 1976. This type of evaluation is based on counting of special factors in thesaurus structure, some of which are counting preferred terms, non preferred terms, cross reference terms and so on. Therefore, various statistical tests have been proposed and applied for evaluation of thesauri. In this article, we try to explain some ratios in the field of unity quantitative evaluation in a thesaurus term network. Theoretical base of the ratios' indicators and indices construction, and epistemological thought in this type of quantitative evaluation, are discussed in this article. The theoretical base of quantitative evaluation is the epistemological thought of Immanuel Kant's Critique of pure reason. The cognition states of transcendental understanding are divided into three steps, the first is perception, the second combination and the third, relation making. Terms relation domains and conceptual relation domains can be analyzed with ratios. The use of quantitative evaluations in current research in the field of thesaurus construction prepares a basis for a restoration period. In modern thesaurus construction, traditional term relations are analyzed in detail in the form of new conceptual relations. Hence, the new domains of hierarchical and associative relations are constructed in the form of relations between concepts. The newly formed conceptual domains can be a suitable basis for quantitative evaluation analysis in conceptual relations.
  6. Xu, G.; Cao, Y.; Ren, Y.; Li, X.; Feng, Z.: Network security situation awareness based on semantic ontology and user-defined rules for Internet of Things (2017) 0.03 
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    Abstract
    Internet of Things (IoT) brings the third development wave of the global information industry which makes users, network and perception devices cooperate more closely. However, if IoT has security problems, it may cause a variety of damage and even threaten human lives and properties. To improve the abilities of monitoring, providing emergency response and predicting the development trend of IoT security, a new paradigm called network security situation awareness (NSSA) is proposed. However, it is limited by its ability to mine and evaluate security situation elements from multi-source heterogeneous network security information. To solve this problem, this paper proposes an IoT network security situation awareness model using situation reasoning method based on semantic ontology and user-defined rules. Ontology technology can provide a unified and formalized description to solve the problem of semantic heterogeneity in the IoT security domain. In this paper, four key sub-domains are proposed to reflect an IoT security situation: context, attack, vulnerability and network flow. Further, user-defined rules can compensate for the limited description ability of ontology, and hence can enhance the reasoning ability of our proposed ontology model. The examples in real IoT scenarios show that the ability of the network security situation awareness that adopts our situation reasoning method is more comprehensive and more powerful reasoning abilities than the traditional NSSA methods. [http://ieeexplore.ieee.org/abstract/document/7999187/]
  7. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.03 
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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.
  8. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.03 
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    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
  9. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.02 
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    Pages
    S.11-22
  10. Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017) 0.02 
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    Date
    13.12.2017 14:17:22
  11. Tudhope, D.; Hodge, G.: Terminology registries (2007) 0.02 
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    Date
    26.12.2011 13:22:07
  12. Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002) 0.02 
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    Date
    30. 5.2010 16:22:35
  13. Nielsen, M.: Neuronale Netze : Alpha Go - Computer lernen Intuition (2018) 0.02 
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    Source
    Spektrum der Wissenschaft. 2018, H.1, S.22-27
  14. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.01 
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    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  15. Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.01 
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    Date
    31. 7.2010 16:58:22
  16. OWL Web Ontology Language Test Cases (2004) 0.01 
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    Date
    14. 8.2011 13:33:22
  17. Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997) 0.01 
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    Date
    1.10.2018 14:13:22
  18. Hauff-Hartig, S.: Wissensrepräsentation durch RDF: Drei angewandte Forschungsbeispiele : Bitte recht vielfältig: Wie Wissensgraphen, Disco und FaBiO Struktur in Mangas und die Humanities bringen (2021) 0.01 
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    Date
    22. 5.2021 12:43:05
  19. Priss, U.: Faceted information representation (2000) 0.01 
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    Date
    22. 1.2016 17:47:06
  20. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005) 0.01 
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    Date
    11. 2.2011 18:22:58

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