Uncertain Ontology-Aware Knowledge Graph Embeddings
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
UOKGE jointly encodes the graph structure and the ontology structure to improve confidence prediction performance.
“UOKGE (Boutouhami et al., 2020) jointly encodes the graph structure and the ontology structure to improve the confidence prediction performance, which however requires an additional ontology of entity types that is not always available to all KGs.”
From Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning (2021) · cites this paper as Boutouhami et al., 2020
UOKGE cannot serve as a baseline because it requires additional ontology information for entities that is not available to these UKGs.
“UOKGE (Boutouhami et al., 2020) cannot serve as a baseline because it requires additional ontology information for entities that is not available to these UKGs.”
From Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning (2021) · cites this paper as Boutouhami et al., 2020
Cites
Complex Embeddings for Simple Link Prediction
Trouillon, T., Welbl, J., Riedel, S., Gaussier, É., & Bouchard, G. (2016) · arXiv · doi:10.48550/arxiv.1606.06357 · Cited by 2,100 · see citing works
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Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning
Chen, X., Boratko, M., Chen, M., Dasgupta, S. S., Li, X. L., & McCallum, A. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/2021.naacl-main.68 · Cited by 47 · see citing works
“UOKGE (Boutouhami et al., 2020) jointly encodes the graph structure and the ontology structure to improve the confidence prediction performance, which however requires an additional ontology of entity types that is not always available to all KGs.”
BackgroundMethodInfluential
- Authors
- Boutouhami, K., Zhang, J., Qi, G., & Gao, H.
- Affiliations
- Southeast University (CN)
- Corresponding author
- Boutouhami, Khaoula
- Qi, Guilin
- Venue
- Communications in Computer and Information Science
- Publisher
- Springer Singapore
- Published
- 2020
- Pages
- 129-136
- ISSN
- 1865-0929 (ISSN-L)
- 1865-0937
- OpenAlex
- W3007853093
- Cited by
- 14
- References
- 1
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 5 · 2023: 1 · 2022: 1 · 2021: 3 · 2020: 1
- FWCI
- 0.57
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Communications in computer and information science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Graph Neural Networks
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Keywords
- knowledge graph embedding, confidence scores
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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