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Outputs (2)

A framework for differentially-private knowledge graph embeddings (2021)
Journal Article
Han, X., Dell’Aglio, D., Grubenmann, T., Cheng, R., & Bernstein, A. (2022). A framework for differentially-private knowledge graph embeddings. Journal of Web Semantics, 72, Article 100696. https://doi.org/10.1016/j.websem.2021.100696

Knowledge graph (KG) embedding methods are at the basis of many KG-based data mining tasks, such as link prediction and node clustering. However, graphs may contain confidential information about people or organizations, which may be leaked via embed... Read More about A framework for differentially-private knowledge graph embeddings.

Geolog: Scalable Logic Programming on Spatial Data (2021)
Presentation / Conference Contribution
Grubenmann, T., & Lehmann, J. (2021). Geolog: Scalable Logic Programming on Spatial Data. In Proceedings ICLP 2021 (191-204). https://doi.org/10.4204/eptcs.345.34

Spatial data is ubiquitous in our data-driven society. The Logic Programming community has been investigating the use of spatial data in different settings. Despite the success of this research, the Geographic Information System (GIS) community has r... Read More about Geolog: Scalable Logic Programming on Spatial Data.