Select two or more frameworks to compare their similarities and differences.
Comparing 1 framework: A Novel Customizing Knowledge Graph Evaluation Method for Incorporating User Needs.
| Field |
A Novel Customizing Knowledge Graph Evaluation Method for Incorporating User Needs. 2024 |
|---|---|
| Year | 2024 |
| Title | A Novel Customizing Knowledge Graph Evaluation Method for Incorporating User Needs. |
| Abstract | Introduces an accuracy-focused KG evaluation method that incorporates user requirements. It designs an effective two-stage weighted cluster sampling (EP-TWCS) to focus on user-important entities. Experiments show the sampled accuracy closely … |
| Objectives | Ensure accuracy assessment of KGs in a cost-saving way that meets specific user requirements. |
| Methodology | EP-TWCS sampling: assigns weights based on user usage frequency and entity popularity, then performs stratified sampling to estimate KG accuracy. |
| Algorithm Used | EP-TWCS (Entity Popularity – Two-stage Weighted Cluster Sampling) |
| Top Model | Sampling-based evaluation |
| Accuracy | Accuracy of sampled assessment nearly equals real accuracy; sample size is minimized. |
| Advantages | User-centric: tailors sampling to what users care about; efficient (minimal sample size) while maintaining accuracy. |
| Drawbacks | Focuses only on the accuracy dimension of quality; requires knowledge of user usage weights; may not address completeness or consistency. |
| Source | https://www.researchgate.net/publication/380129766_A_novel_customizing_knowledge_graph_evaluation_method_for_incorporating_user_needs#full-text |
| Total Criteria | 6 |
Comparing 6 unique criteria across selected frameworks.
✨ AI-powered semantic analysis enabled
| Criterion |
A Novel Customizing Knowledge Graph Evaluation Method for Incorporating User Needs. 2024 |
|---|---|
| Accuracy |
✓ Included
Description: This criterion measures the accuracy of knowledge graph data by assessing the correctness of facts and the accuracy of relationships within the graph, with a focus on user-important entities selected … Definitions:
|
| Relevancy (User Needs |
✓ Included
Description: This criterion measures the relevancy of entities in the knowledge graph by evaluating how well they align with user needs, as determined through the framework's two-stage weighted cluster sampling (EP-TWCS) … Definition:
|
| Relevancy (User Needs) |
✓ Included
Description: Quality dimension from A Novel Customizing Knowledge Graph Evaluation Method for Incorporating User Needs. Definition:
|
| Timeliness (Efficiency |
✓ Included
Description: This criterion measures the timeliness or efficiency of a knowledge graph by evaluating the accuracy of the sampled entities in relation to the true accuracy, with the goal of minimizing … Definition:
|
| Timeliness (Efficiency) |
✓ Included
Description: Quality dimension from A Novel Customizing Knowledge Graph Evaluation Method for Incorporating User Needs. Definition:
|
| Value added |
✓ Included
Description: Measures the additional value that the knowledge graph provides beyond basic data storage. Definitions:
|