Search (48 results, page 1 of 3)

  • × year_i:[2020 TO 2030}
  • × theme_ss:"Wissensrepräsentation"
  1. Jia, J.: From data to knowledge : the relationships between vocabularies, linked data and knowledge graphs (2021) 0.02 
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    Date
    22. 1.2021 14:24:32
    Language
    e
  2. Hocker, J.; Schindler, C.; Rittberger, M.: Participatory design for ontologies : a case study of an open science ontology for qualitative coding schemas (2020) 0.01 
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    Date
    20. 1.2015 18:30:22
    Language
    e
  3. 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
  4. 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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    Abstract
    Nos últimos 30 anos, o tema das ontologias tem sido um dos terrenos mais férteis de investigação na área da Organização do Conhecimento. É um tema complexo e revestido de polémica, pela dificuldade na definição do próprio conceito e pelas apropriações que diferentes campos científicos têm exercido sobre ele. Com origem no domínio da filosofia, a ontologia é hoje um território partilhado pelas Ciências da Computação, com destaque para a Ciência dos Dados (Data Science), e pela Ciência da Informação, particularmente pela Organização do Conhecimento. São raros os autores desta área que não escreveram sobre o tema, abordando as suas fronteiras conceptuais ou discutindo a relação das ontologias com outros sistemas de organização do conhecimento, como as taxonomias, os tesauros ou as classificações.
  5. Bardhan, S.; Dutta, B.: ONCO: an ontology model for MOOC platforms (2022) 0.00 
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    Abstract
    In the process of searching for a particular course on e-learning platforms, it is required to browse through different platforms, and it becomes a time-consuming process. To resolve the issue, an ontology has been developed that can provide single-point access to all the e-learning platforms. The modelled ONline Course Ontology (ONCO) is based on YAMO, METHONTOLOGY and IDEF5 and built on the Protégé ontology editing tool. ONCO is integrated with sample data and later evaluated using pre-defined competency questions. Complex SPARQL queries are executed to identify the effectiveness of the constructed ontology. The modelled ontology is able to retrieve all the sampled queries. The ONCO has been developed for the efficient retrieval of similar courses from massive open online course (MOOC) platforms.
    Language
    e
  6. Kleineberg, M.: Classifying perspectives : expressing levels of knowing in the Integrative Levels Classification (2020) 0.00 
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  7. Balakrishnan, U,; Soergel, D.; Helfer, O.: Representing concepts through description logic expressions for knowledge organization system (KOS) mapping (2020) 0.00 
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  8. Collard, J.; Paiva, V. de; Fong, B.; Subrahmanian, E.: Extracting mathematical concepts from text (2022) 0.00 
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  9. 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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    Abstract
    Mining product reviews and sentiment analysis are of great significance, whether for academic research purposes or optimizing business strategies. We propose a feature-level sentiment analysis framework based on rules parsing and fine-grained domain ontology for Chinese reviews. Fine-grained ontology is used to describe synonymous expressions of product features, which are reflected in word changes in online reviews. First, a semiautomatic construction method is developed by using Word2Vec for fine-grained ontology. Then, featurelevel sentiment analysis that combines rules parsing and the fine-grained domain ontology is conducted to extract explicit and implicit features from product reviews. Finally, the domain sentiment dictionary and context sentiment dictionary are established to identify sentiment polarities for the extracted feature-sentiment combinations. An experiment is conducted on the basis of product reviews crawled from Chinese e-commerce websites. The results demonstrate the effectiveness of our approach.
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  10. Machado, L.; Veronez Júnior, W.R.; Martínez-Ávila, D.: ¬A indeterminação ontológica dos conceitos : interpretações linguísticas e psicológicas [The ontologic indetermination of concepts: linguistic and psychological interpretations] (2022) 0.00 
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    Source
    Organização e representação do conhecimento em múltiplas abordagens, Chap. 3
  11. Soshnikov, D.: ROMEO: an ontology-based multi-agent architecture for online information retrieval (2021) 0.00 
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  12. Jansen, B.; Browne, G.M.: Navigating information spaces : index / mind map / topic map? (2021) 0.00 
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  13. Favato Barcelos, P.P.; Sales, T.P.; Fumagalli, M.; Guizzardi, G.; Valle Sousa, I.; Fonseca, C.M.; Romanenko, E.; Kritz, J.: ¬A FAIR model catalog for ontology-driven conceptual modeling research (2022) 0.00 
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  14. Hudon, M.: Facet (2020) 0.00 
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  15. Frey, J.; Streitmatter, D.; Götz, F.; Hellmann, S.; Arndt, N.: DBpedia Archivo : a Web-Scale interface for ontology archiving under consumer-oriented aspects (2020) 0.00 
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  16. Biagetti, M.T.: Ontologies as knowledge organization systems (2021) 0.00 
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  17. Gladun, A.; Rogushina, J.: Development of domain thesaurus as a set of ontology concepts with use of semantic similarity and elements of combinatorial optimization (2021) 0.00 
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  18. Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021) 0.00 
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  19. Simoes, G.; Machado, L.; Gnoli, C.; Souza, R.: Can an ontologically-oriented KO do without concepts? (2020) 0.00 
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  20. Tramullas, J.; Garrido-Picazo, P.; Sánchez-Casabón, A.I.: Use of Wikipedia categories on information retrieval research : a brief review (2020) 0.00 
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