Knowledge triple extraction in cybersecurity with adversarial active learning
Aiming at the problem that using pipeline methods for extracting cybersecurity knowledge triples may cause the errors propagation of entity recognition and did not consider the correlation between entity recognition and relation extraction,and training triple extraction model lacked labeled corpora,...
Saved in:
| Main Authors: | Tao LI, Yuanbo GUO, Ankang JU |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2020-10-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/thesisDetails#10.11959/j.issn.1000-436x.2020174 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Knowledge triple extraction in cybersecurity with adversarial active learning
by: Tao LI, et al.
Published: (2020-10-01) -
Research on Spurious-Negative Sample Augmentation-Based Quality Evaluation Method for Cybersecurity Knowledge Graph
by: Bin Chen, et al.
Published: (2024-12-01) -
Generative Adversarial Networks for Dynamic Cybersecurity Threat Detection and Mitigation
by: William Villegas-Ch, et al.
Published: (2025-04-01) -
Research on Parameter-Efficient Knowledge Graph Completion Methods and Their Performance in the Cybersecurity Field
by: Bin Chen, et al.
Published: (2025-01-01) -
Voluntary cybersecurity risk disclosures and firms’ characteristics: the moderating role of the knowledge-intensive industry
by: Harmandeep Singh
Published: (2025-03-01)