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Knowledge Graphs

📅 July 2, 2021 👤 Aidan Hogan, Eva Blomqvist, Michael Cochez et al. 📖 ACM Computing Surveys 📊 1,529 citations

🤖 Plain-English Summary

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.

🔑 Key Findings

  • After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs.
  • We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques.
  • We conclude with high-level future research directions for knowledge graphs.

💡 Why This Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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📋 Article Details

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

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