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How Does Knowledge Evolve in Open Knowledge Graphs?
Abstract
Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically this central aspect of evolution in KGs. To this end, we discuss (i) the dimensions of evolution in KGs, (ii) the observability of evolution in existing, open, collaboratively constructed Knowledge Graphs over time, and (iii) possible metrics to analyse this evolution. We provide an overview of relevant state-of-the-art research, ranging from metrics developed for Knowledge Graphs specifically to potential methods from related fields such as network science. Additionally, we discuss technical approaches - and their current limitations - related to storing, analysing and processing large and evolving KGs in terms of handling typical KG downstream tasks.
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Cites
Temporal Knowledge Graph Completion: A Survey
Cai, B., Xiang, Y., Gao, L., Zhang, H., Li, Y., & Li, J. (2023) · Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2023/734 · Cited by 133
Metadata
- Authors
- Polleres, A., Pernisch, R., Bonifati, A., Dell'Aglio, D., Dobriy, D., Dumbrava, S., Etcheverry, L., Ferranti, N., Hose, K., Jiménez-Ruiz, E., Lissandrini, M., Scherp, A., Tommasini, R., & Wachs, J.
- Venue
- Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- Publisher
- Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- Published
- 2023
- References
- 1
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