Main differences among the methodology chosen “cascade method”, which was influenced by the heterogeneous OC systems in the United Kingdom, and the model SBERT regarding the level of granularity and the consistency of the results, at difference of CASCOT, where both systems SOC and ISCO have a similar level of granularity, and OIM as a merging of concepts
| Cascade method | CASCOT | OIM |
|---|---|---|
| Hierarchical analysis, semantic mapping (NLP models) and benchmarking | Input SOC job titles, output ISCO codes. Based on a probability score (1–100), depending on the similarity algorithms | Mapping and Integration process (merging concepts). To sub-categorize in a significant way the existing ontological categories |
| Validation: Manual (100 samples/dataset, 2 annotators, Kappa 0.23–0.67) | Validation: Rule-based matching | Validation: Conceptual merging |
| Focus: UK healthcare sector, 4 NHS systems | Focus: General SOC-ISCO mapping | Focus: Generic ontology integration |
| Cascade method | CASCOT | OIM |
|---|---|---|
| Hierarchical analysis, semantic mapping (NLP models) and benchmarking | Input SOC job titles, output ISCO codes. Based on a probability score (1–100), depending on the similarity algorithms | Mapping and Integration process (merging concepts). To sub-categorize in a significant way the existing ontological categories |
| Validation: Manual (100 samples/dataset, 2 annotators, Kappa 0.23–0.67) | Validation: Rule-based matching | Validation: Conceptual merging |
| Focus: UK healthcare sector, 4 NHS systems | Focus: General SOC-ISCO mapping | Focus: Generic ontology integration |
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