CGNN-MGS: A Cascaded Heterogeneous Graph Neural Network With Meta-Path Ring Structures for Joint Modeling of Contract Clause Text and Structural Dependencies
- DOI
- 10.1109/access.2026.3722487
- Published
- 2026
- Container
- IEEE Access
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/access.2026.3722487,
title = {CGNN-MGS: A Cascaded Heterogeneous Graph Neural Network With Meta-Path Ring Structures for Joint Modeling of Contract Clause Text and Structural Dependencies},
author = {Xi Liu and Ru Wang},
year = {2026},
journal = {IEEE Access},
doi = {10.1109/access.2026.3722487},
url = {https://doi.org/10.1109/access.2026.3722487}
}RIS
TY - JOUR TI - CGNN-MGS: A Cascaded Heterogeneous Graph Neural Network With Meta-Path Ring Structures for Joint Modeling of Contract Clause Text and Structural Dependencies AU - Xi Liu AU - Ru Wang PY - 2026 JO - IEEE Access DO - 10.1109/access.2026.3722487 UR - https://doi.org/10.1109/access.2026.3722487 ER -
APA
Liu, X., & Wang, R. (2026). CGNN-MGS: A Cascaded Heterogeneous Graph Neural Network With Meta-Path Ring Structures for Joint Modeling of Contract Clause Text and Structural Dependencies. IEEE Access. https://doi.org/10.1109/access.2026.3722487
Source records
- crossref · retrieved 2026-11-10T09:12:52.380Z