# Structural Quality Metrics to Evaluate Knowledge Graphs

arXiv: https://arxiv.org/abs/2211.10011 · HTML: https://mlsanity.com/paper/2211.10011/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 32 references that are in the map.
- First posted on arXiv 18 Nov 2022.

## Builds on (most cited first, 4 of 4)

- [A Survey on Knowledge Graph-Based Recommender Systems](https://mlsanity.com/paper/2003.00911/) (2020)
- [Knowledge Graphs on the Web -- an Overview](https://mlsanity.com/paper/2003.00719/) (2020)
- [Which Knowledge Graph Is Best for Me?](https://mlsanity.com/paper/1809.11099/) (2018)
- [OK Google, What Is Your Ontology? Or: Exploring Freebase Classification to Understand Google's Knowledge Graph](https://mlsanity.com/paper/1805.03885/) (2018)

## Built on by (most cited first, 2 of 2)

- [From Patient Consultations to Graphs: Leveraging LLMs for Patient Journey Knowledge Graph Construction](https://mlsanity.com/paper/2503.16533/) (2025)
- [Evaluating Knowledge Graph Complexity via Semantic, Spectral, and Structural Metrics for Link Prediction](https://mlsanity.com/paper/2508.15291/) (2025)

## Abstract (arXiv)

This work presents six structural quality metrics that can measure the quality of knowledge graphs and analyzes five cross-domain knowledge graphs on the web (Wikidata, DBpedia, YAGO, Google Knowledge Graph, Freebase) as well as 'Raftel', Naver's integrated knowledge graph. The 'Good Knowledge Graph' should define detailed classes and properties in its ontology so that knowledge in the real world can be expressed abundantly. Also, instances and RDF triples should use the classes and properties actively. Therefore, we tried to examine the internal quality of knowledge graphs numerically by focusing on the structure of the ontology, which is the schema of knowledge graphs, and the degree of use thereof. As a result of the analysis, it was possible to find the characteristics of a knowledge graph that could not be known only by scale-related indicators such as the number of classes and properties.