Select two or more frameworks to compare their similarities and differences.
Comparing 1 framework: Structural Quality Metrics to Evaluate Knowledge Graph Quality
| Field |
Structural Quality Metrics to Evaluate Knowledge Graph Quality 2022 |
|---|---|
| Year | 2022 |
| Title | Structural Quality Metrics to Evaluate Knowledge Graph Quality |
| Abstract | Presents six structural quality metrics (ICR, IPR, CI, IMI, SPA, SPI) to evaluate KGs based on the specificity and active usage of the underlying ontology (structure). |
| Objectives | To devise a measure to compare KG quality based on the premise that structure (=ontology) is a key factor, moving beyond metrics focused solely on size/distribution. |
| Methodology | Defined and applied six structural quality metrics to compare six cross-domain KGs (Wikidata, DBpedia, YAGO, Freebase, Google KG, Raftel). |
| Algorithm Used | Statistical measures of ontology structure (ICR, IPR, CI, IMI, SPA, SPI) |
| Top Model | Structural Metrics Model |
| Accuracy | N/A (Structural comparison) |
| Advantages | Provides a novel viewpoint linking quality directly to schema richness and usage; effective for comparative, high-level assessment. |
| Drawbacks | Focuses on schema quality (T-box); generally omits instance-level semantic correctness; technical part (formal property definition) can be improved. |
| Source | https://www.researchgate.net/publication/365616417_Structural_Quality_Metrics_to_Evaluate_Knowledge_Graphs#full-text |
| Total Criteria | 5 |
Comparing 5 unique criteria across selected frameworks.
✨ AI-powered semantic analysis enabled
The following criteria are semantically similar (same concept, different names):
| Criterion |
Structural Quality Metrics to Evaluate Knowledge Graph Quality 2022 |
|---|---|
| Concise representation |
✓ Included
Description: Presents six structural quality metrics (ICR, IPR, CI, IMI, SPA, SPI) to evaluate KGs based on the specificity and active usage of the underlying ontology (structure). (2022) Definitions:
🤖 AI-Enhanced Description:
Concise representation in the framework Structural Quality Metrics to Evaluate Knowledge Graph Quality refers to the degree to which the knowledge graph's structure is organized in a way that minimizes redundancy and maximizes the precision of its underlying ontology. This criterion is measured by assessing the number of distinct concepts and their relationships that are represented in a compact and organized manner, without unnecessary duplication or fragmentation. The practical significance of this criterion lies in its ability to evaluate the efficiency of the knowledge graph's structure in conveying meaningful information, which is essential for effective knowledge graph reasoning and inference. |
| Consistent representation |
✓ Included
Description: Presents six structural quality metrics (ICR, IPR, CI, IMI, SPA, SPI) to evaluate KGs based on the specificity and active usage of the underlying ontology (structure). (2022) Definitions:
|
| Ease of understanding |
✓ Included
Description: Presents six structural quality metrics (ICR, IPR, CI, IMI, SPA, SPI) to evaluate KGs based on the specificity and active usage of the underlying ontology (structure). (2022) Definitions:
|
| Interpretability |
✓ Included
Description: Presents six structural quality metrics (ICR, IPR, CI, IMI, SPA, SPI) to evaluate KGs based on the specificity and active usage of the underlying ontology (structure). (2022) Definitions:
|
| Structural Consistency |
✓ Included
Description: Presents six structural quality metrics (ICR, IPR, CI, IMI, SPA, SPI) to evaluate KGs based on the specificity and active usage of the underlying ontology (structure). (2022) Definitions:
|