Research map / Label-efficient and robust learning / OOD and anomaly detection
Unsupervised Detection of Sub-Events in Large Scale Disasters
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use ontology-based semantic ranking and filtering instead of DEPSUB ranking | Sub-event detection · Hurricane Harvey | F1-score | Helped |
| Use ontology-based semantic ranking and filtering instead of DEPSUB ranking | Sub-event detection · Nepal Earthquake | F1-score | Helped |
| Add phrase candidates to noun-verb pairs (ablation) | MOAC+NV sub-event detection · Hurricane Harvey | F1-score | Helped |
| Add phrase candidates to noun-verb pairs (ablation) | MOAC+NV sub-event detection · Nepal Earthquake | F1-score | Helped |
| Filter noun-verb pairs to those occurring more than once (ablation) | Proposed sub-event detection · Hurricane Harvey | F1-score | Helped |
| Filter noun-verb pairs to those occurring more than once (ablation) | Proposed sub-event detection · Nepal Earthquake | F1-score | Helped |
| Cluster ranked sub-events with spectral clustering | Proposed method · Hurricane Harvey tweet collections | average number of labels: 2.11 -> 2.00 | Helped |
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