google-research/smore

Extending the SMORE framework at both dataset and operator levels

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ZHANGWENTAI commented

Background

SMORE has 6 algorithms for knowledge graph reasoning so far. However, it still has some limitations. For example, it limits in using type information of triple-based KG, and reasoning on Temporal KG and Hyper-relational KG.

Goal

We are going to extend SMORE to support three more algorithms in different categories:

  • TeMP, which can levarage the type information of Knowledge Graph;
  • TFLEX on Temporal Knowledge Graph;
  • NQE on Hyper-relational Knowledge Graph

In detail, we plan to integrate different types of knowledge graph datasets, and different operators.

TODOs

  • TeMP
  • TFLEX
  • NQE

References

[1] Hu, Zhiwei, et al. "Type-aware embeddings for multi-hop reasoning over knowledge graphs." arXiv preprint arXiv:2205.00782 (2022).

[2] Lin, Xueyuan, et al. "TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph." arXiv preprint arXiv:2205.14307 (2022).

[3] Luo, Haoran, et al. "Nqe: N-ary query embedding for complex query answering over hyper-relational knowledge graphs." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 37. No. 4. 2023.

Hanjun-Dai commented

Hi Wentai,

Thank you so much for sharing this proposal!
We look forward to your contributions, and please let us know if you encounter any issue during the development.

Best,
Hanjun

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