Logical Foundations of Linked Data Anonymisation
Article Properties
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DOI (url)
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Publication Date2019/02/16
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Indian UGC (journal)
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Citations4
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Bernardo Cuenca Grau
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Egor V. Kostylev
Abstract
Cite
Grau, Bernardo Cuenca, and Egor V. Kostylev. “Logical Foundations of Linked Data Anonymisation”. Journal of Artificial Intelligence Research, vol. 64, 2019, pp. 253-14, https://doi.org/10.1613/jair.1.11355.
Grau, B. C., & Kostylev, E. V. (2019). Logical Foundations of Linked Data Anonymisation. Journal of Artificial Intelligence Research, 64, 253-314. https://doi.org/10.1613/jair.1.11355
Grau BC, Kostylev EV. Logical Foundations of Linked Data Anonymisation. Journal of Artificial Intelligence Research. 2019;64:253-314.
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
A review of reasoning characteristics of RDF‐based Semantic Web systems | WIREs Data Mining and Knowledge Discovery |
| 2024 | |
A Gentle Introduction to Controlled Query Evaluation in DL-Lite Ontologies | SN Computer Science | 2024 | ||
| A false sense of security | Artificial Intelligence |
| 1 | 2022 |
Reasoning in Description Logic Ontologies for Privacy Management | KI - Künstliche Intelligenz |
| 1 | 2020 |
Citations Analysis
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 3
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Reasoning in Description Logic Ontologies for Privacy Management and was published in 2020. The most recent citation comes from a 2024 study titled A review of reasoning characteristics of RDF‐based Semantic Web systems. This article reached its peak citation in 2024, with 2 citations. It has been cited in 4 different journals. Among related journals, the WIREs Data Mining and Knowledge Discovery cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.