Domain-specific Knowledge Graphs: A survey

By Bilal Abu-Salih. Journal of Network and Computer Applications, 2020

378 citations recorded by the source corpus.

Knowledge Graphs (KGs) have made a qualitative leap and effected a real revolution in knowledge representation. This is leveraged by the underlying structure of the KG which underpins a better comprehension, reasoning and interpreting of knowledge for both human and machine. Therefore, KGs continue to be used as a main driver to tackle a plethora of real-life problems in dissimilar domains. However, there is no consensus on a plausible and definition to domain KG. Further, in conjunction with several limitations and deficiencies, various domain KG construction approaches are far from perfection. This survey is the first to provide an inclusive definition to the notion of domain KG. Also, a comprehensive review of the state-of-the-art approaches drawn from academic works relevant to seven dissimilar domains of knowledge is provided. The scrutiny of the current approaches reveals a correlated array of limitations and deficiencies. The set of improvements made to address the limitations of the current approaches are introduced followed by recommendations and opportunities for future research directions.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/b2e0f559cc6e1398830f6feafa846a26ab4c234e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Feng Xia
2. Linhao Luo
3. Ciyuan Peng
4. Xindong Wu
5. Francesco Osborne
6. Chen Chen
7. Mehdi Naseriparsa
8. Jiapu Wang

In Computational Theory and Mathematics

1. Ciyuan Peng
2. Xindong Wu
3. Francesco Osborne
4. Feng Xia
5. Mehdi Naseriparsa
6. Shirui Pan

Citations in the corpus

• Knowledge Graphs: Opportunities and Challenges (2023, methodology): “These models successfully utilized knowledge graphs in many different domains, including digital libraries (Yao et al. 2017), biomedical (Harnoune et al. 2021), social media (Abu-Salih 2021), and scientific research (Nayyeri et al. 2021).”
• Unifying Large Language Models and Knowledge Graphs: A Roadmap (2023, background): “Additionally, experts can construct domain-specific KGs to provide precise and dependable domain-specific knowledge [23].”