A Multi-threaded Framework for Integrating Knowledge into a Biomedical Knowledge Graph
Le Van Thanh, Pham Van Hai, Cu Kim Long, Duong Vu Tuan Minh, Nguyen Hai Anh, Tran Minh Dung
Lecture notes in networks and systems
Problems Identified (4)
Biomedical heterogeneous data integration: Biomedical research faces heterogeneous data at large scale, creating a need for robust integration and insight-extraction systems.
Underutilized biomedical knowledge graphs: Knowledge graphs are described as powerful but underutilized in biomedicine.
Biomedical heterogeneous data integration: Biomedical research faces heterogeneous data at large scale, creating a need for robust integration and insight-extraction systems.
Underutilized biomedical knowledge graphs: Knowledge graphs are described as powerful but underutilized in biomedicine.
Proposed Solutions (2)
Multi-threaded BioKG integration framework: The paper proposes a multi-threaded method to enrich biomedical knowledge graphs with semantic entities from the BioKG dataset.
Multi-threaded BioKG integration framework: The paper proposes a multi-threaded method to enrich biomedical knowledge graphs with semantic entities from the BioKG dataset.
Results (2)
Biomedical entity crawling resource:
Biomedical entity crawling resource:
Research Domain
Biomedical knowledge graphs and data integration