Search (25 results, page 1 of 2)

  • × theme_ss:"Wissensrepräsentation"
  • × year_i:[2020 TO 2030}
  1. 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
  2. Jia, J.: From data to knowledge : the relationships between vocabularies, linked data and knowledge graphs (2021) 0.00 
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    Date
    22. 1.2021 14:24:32
  3. Hocker, J.; Schindler, C.; Rittberger, M.: Participatory design for ontologies : a case study of an open science ontology for qualitative coding schemas (2020) 0.00 
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    Date
    20. 1.2015 18:30:22
  4. Wei, W.; Liu, Y.-P.; Wei, L-R.: Feature-level sentiment analysis based on rules and fine-grained domain ontology (2020) 0.00 
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    Content
    DOI:10.5771/0943-7444-2020-2-105.
    Date
    2. 9.2014 19:19:40
    Source
    Knowledge organization. 47(2020) no.2, S.105-121
  5. Biagetti, M.T.: Ontologies as knowledge organization systems (2021) 0.00 
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    Date
    2. 9.2014 19:19:40
    Source
    Knowledge organization. 48(2021) no.2, S.152-176
  6. Sinha, P.K.; Dutta, B.: ¬A systematic analysis of flood ontologies : a parametric approach (2020) 0.00 
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    Content
    DOI:10.5771/0943-7444-2020-2-138.
    Date
    2. 9.2014 19:19:40
    Source
    Knowledge organization. 47(2020) no.2, S.138-159
  7. MacFarlane, A.; Missaoui, S.; Frankowska-Takhari, S.: On machine learning and knowledge organization in multimedia information retrieval (2020) 0.00 
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    Abstract
    Recent technological developments have increased the use of machine learning to solve many problems, including many in information retrieval. Multimedia information retrieval as a problem represents a significant challenge to machine learning as a technological solution, but some problems can still be addressed by using appropriate AI techniques. We review the technological developments and provide a perspective on the use of machine learning in conjunction with knowledge organization to address multimedia IR needs. The semantic gap in multimedia IR remains a significant problem in the field, and solutions to them are many years off. However, new technological developments allow the use of knowledge organization and machine learning in multimedia search systems and services. Specifically, we argue that, the improvement of detection of some classes of lowlevel features in images music and video can be used in conjunction with knowledge organization to tag or label multimedia content for better retrieval performance. We provide an overview of the use of knowledge organization schemes in machine learning and make recommendations to information professionals on the use of this technology with knowledge organization techniques to solve multimedia IR problems. We introduce a five-step process model that extracts features from multimedia objects (Step 1) from both knowledge organization (Step 1a) and machine learning (Step 1b), merging them together (Step 2) to create an index of those multimedia objects (Step 3). We also overview further steps in creating an application to utilize the multimedia objects (Step 4) and maintaining and updating the database of features on those objects (Step 5).
    Date
    2. 9.2014 19:19:40
  8. Hudon, M.: Facet (2020) 0.00 
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    Date
    2. 9.2014 19:19:40
  9. Banerjee, D.; Ghosh, S.S.; Mondal, T.M.: OnE : an ontology evaluation framework (2020) 0.00 
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    2. 9.2014 19:19:40
  10. Rocha Souza, R.; Lemos, D.: a comparative analysis : Knowledge organization systems for the representation of multimedia resources on the Web (2020) 0.00 
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    2. 9.2014 19:19:40
  11. Gnoli, C.: Faceted classifications as linked data : a logical analysis (2021) 0.00 
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    2. 9.2014 19:19:40
  12. Zhitomirsky-Geffet, M.; Avidan, G.: ¬A new framework for systematic analysis and classification of inconsistencies in multi-viewpoint ontologies (2021) 0.00 
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    2. 9.2014 19:19:40
  13. Almeida, M.B.: Ontologia em Ciência da Informação: Teoria e Método (1ª ed., Vol. 1). CRV. http://dx.doi.org/10.24824/978655578679.8; Tecnologia e Aplicações (1ª ed., Vol. 2). CRV. http://dx.doi.org/10.24824/978652511477.4; Curso completo com teoria e exercícios (1ª ed., volume suplementar para professores). CRV. [Review] (2022) 0.00 
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  14. Bardhan, S.; Dutta, B.: ONCO: an ontology model for MOOC platforms (2022) 0.00 
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    2. 9.2014 19:19:40
  15. Jiang, Y.-C.; Li, H.: ¬The theoretical basis and basic principles of knowledge network construction in digital library (2023) 0.00 
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  16. Meng, K.; Ba, Z.; Ma, Y.; Li, G.: ¬A network coupling approach to detecting hierarchical linkages between science and technology (2024) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 75(2023) no.2, S.167-187
  17. Ghosh, S.S.; Das, S.; Chatterjee, S.K.: Human-centric faceted approach for ontology construction (2020) 0.00 
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    2. 9.2014 19:19:40
  18. Oliveira Machado, L.M.; Almeida, M.B.; Souza, R.R.: What researchers are currently saying about ontologies : a review of recent Web of Science articles (2020) 0.00 
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  19. Amirhosseini, M.; Avidan, G.: ¬A dialectic perspective on the evolution of thesauri and ontologies (2021) 0.00 
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  20. Broughton, V.: Science and knowledge organization : an editorial (2021) 0.00 
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    2. 9.2014 19:19:40

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