Research map / Learning theory and algorithms / Clustering
Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use F-MWSP instead of hierarchical clustering | Entity resolution on patent_example · patent_example | F1 measure: 92.2% -> 94.8% | Helped |
| Use F-MWSP instead of hierarchical clustering | Entity resolution on patent_example · patent_example | Precision: 95.5% -> 95.4% | No clear effect |
| Use F-MWSP instead of hierarchical clustering | Entity resolution on patent_example · patent_example | Recall: 89.1% -> 94.3% | Helped |
| Use Flexible DOIs instead of Varying DOIs | F-MWSP · patent_example | speedup: at least 20% | Helped |
| Increase the number of Flexible DOI thresholds | F-MWSP · patent_example | speedup: up to 60% | Helped |
| Use heuristic pricing instead of exact pricing | F-MWSP · patent_example | computation time: atleast 1 hour -> about 20 seconds | Helped |
| Use F-MWSP instead of hierarchical clustering | Entity resolution · csv_example | F1 score: 94.4% -> 95.2 % | Helped |
| Use F-MWSP clustering | Entity resolution · Settlements | F1 score: 0.92 -> 0.96 | Helped |
| Use F-MWSP clustering | Entity resolution · Music 20K | F1 score: 0.74 -> 0.81 | Helped |
Closest papers by meaning
- Multipartite Entity Resolution: Motivating a K-Tuple Perspective (Student Abstract) (AAAI 2024 · similarity 0.86)
- Flexible Models for Microclustering with Application to Entity Resolution (NeurIPS 2016 · similarity 0.82)
- Upper Bounding Barlow Twins: A Novel Filter for Multi-Relational Clustering (AAAI 2024 · similarity 0.82)
- Improving the Efficiency and Effectiveness for BERT-based Entity Resolution (AAAI 2021 · similarity 0.82)
- Competitively Consistent Clustering (ICML 2025 · similarity 0.81)
- Expected Probabilistic Hierarchies (NeurIPS 2024 · similarity 0.81)
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