ICDM 2019 Knowledge Graph Contest: Team UWA
Not on the map. Why?
Abstract (arXiv)
We present an overview of our triple extraction system for the ICDM 2019 Knowledge Graph Contest. Our system uses a pipeline-based approach to extract a set of triples from a given document. It offers a simple and effective solution to the challenge of knowledge graph construction from domain-specific text. It also provides the facility to visualise useful information about each triple such as the degree, betweenness, structured relation type(s), and named entity types.
Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). First posted on arXiv 4 Sep 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 3; 2022: 0; 2023: 1.
4 papers.
- 2021A Survey on State-of-the-art Techniques for Knowledge Graphs Construction and Challenges aheadcited by 4
- 2023DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Researchcited by 2
- 2021Textbook to triples: Creating knowledge graph in the form of triples from AI TextBookcited by 1
- 2021Knowledge mining of unstructured information: application to cyber-domaincited by 0
- 2023DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research4 Sep 2023
- 2021Textbook to triples: Creating knowledge graph in the form of triples from AI TextBook20 Nov 2021
- 2021A Survey on State-of-the-art Techniques for Knowledge Graphs Construction and Challenges ahead15 Oct 2021
- 2021Knowledge mining of unstructured information: application to cyber-domain8 Sep 2021