Metaknowledge Extraction Based on Multi-Modal Documents
The triplet-based knowledge in large-scale knowledge bases is most likely lacking in structural logic and problematic of conducting knowledge hierarchy. In this paper, we introduce the concept of metaknowledge to knowledge engineering research for the purpose of structural knowledge construction. Th...
Saved in:
Main Authors: | Shu-Kan Liu, Rui-Lin Xu, Bo-Ying Geng, Qiao Sun, Li Duan, Yi-Ming Liu |
---|---|
Format: | article |
Language: | EN |
Published: |
IEEE
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/a8ccb9c6d91348e882481d887a4bde28 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Accurate Fine-Grained Layout Analysis for the Historical Tibetan Document Based on the Instance Segmentation
by: Penghai Zhao, et al.
Published: (2021) -
Deep Learning in Time-Frequency Domain for Document Layout Analysis
by: Felipe Grijalva, et al.
Published: (2021) -
Progressive Guided Fusion Network With Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection
by: Jiajia Wu, et al.
Published: (2021) -
Development Strategy for Air–Ground Collaborative Multi-Modal Intelligent Robot System
by: Huang Qiang, Meng Fei, Yu Zhangguo, Lin Defu, Xu Bin, Duo Yingxian
Published: (2021) -
Multi-modal Deep Learning and Its Applications in Ophthalmic Artificial Intelligence
by: LI Xirong
Published: (2021)