In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques.
This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.
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| Category | 🤖 Artificial Intelligence |
| Published | Jul 02, 2021 |
| Journal | ACM Computing Surveys |
| Authors | Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d’Amato, Gerard de Melo |
| DOI | 10.1145/3447772 |
| Citations | 1,529 |
| Source | OpenAlex |