Uncovering Hidden Connections: Granular Relationship Analysis in Knowledge Graphs

Author:

Romanova AlexORCID

Publisher

Springer Nature Singapore

Reference19 articles.

1. Bronstein M, Bruna J, Cohen T, Veliˇckovi´c P (2021) Geomet-ric deep learning: grids, groups, graphs, geodesics, and gauges. https://doi.org/10.48550/arXiv.2104.13478

2. Castellano G, Sansaro G, Vessio G (2021) Integrating contextual knowledge to visual features for fine art classification DL4KG’21: workshop on deep learning for knowledge graphs

3. Find Semantic Similarities by GNN Link Predictions: Continue rewiring knowledge graphs (2022) http://sparklingdataocean.com/2022/11/09/knowledgeGraph4NlpGnn/

4. Garcia N, Renoust B, Nakashima Y (2020) ContextNet: representation and exploration for painting classification and retrieval in context. Int J Multimedia Inf Retrieval. https://doi.org/10.1007/s13735-019-00189-4

5. Hamilton W, Ying Z, Leskovec J (2017) Inductive representation learning on large graphs. Adv Neural Inf Process Syst 30(NIPS 2017). arXiv:1706.02216

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