| Issue |
SHS Web Conf.
Volume 181, 2024
2023 International Conference on Digital Economy and Business Administration (ICDEBA 2023)
|
|
|---|---|---|
| Article Number | 03022 | |
| Number of page(s) | 14 | |
| Section | Supply Chain Management and Logistics | |
| DOI | https://doi.org/10.1051/shsconf/202418103022 | |
| Published online | 17 January 2024 | |
A Knowledge Graph Data Expansion Method Based on Relational Propensity Categories with Legal Applications
1 Zhejiang Gongshang University Hangzhou College of Commerce, Hangzhou 311599, China
2 School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China
* Corresponding author: mengshi@zjgsu.edu.cn
By introducing the definition of propensity categories of relations, the implicit information in the knowledge graph is mined and the MCBE (Maximum Clique Based Expansion) algorithm is used for data expansion. Experimental results show that with baseline models TransE, RotatE, HAKE and Complex on FB15K dataset, its MRR and Hits@1 metrics are improved by (7.9%, 9.6%), (4.2%, 3.3%), (2.7%, 4.8%) and (1.7%, 2.4%), respectively. Experiments are also conducted on the FB15K, YAGO3-10, NELL-995 and DBpedia50 datasets using the TransE model as a baseline, and its MRR and Hits@1 metrics are improved on the above datasets by (7.9%, 9.6%), (0.3%, 27.7%), (20.1%, 100%), (4%, 38.7%), respectively. Finally, the MCBE algorithm is applied to the self-constructed knowledge graph of “anti-drug law” and its MRR and Hits@1 metrics are improved by (10.6%, 12.3%). The experimental results show that MCBE algorithm improves the prediction accuracy of legal knowledge graph.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.