Aggregating Semantic Annotators
Summary: Ontology-aware aggregation unifies diverse semantic annotators into a richer annotation layer. A training-free, repair-based method, benchmarked against supervised models and ontology-unaware baselines, improves accuracy via inter-annotator signals. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Luying Chen
- 2. Stefano Ortona
- 3. Giorgio Orsi
- 4. Michael Benedikt
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,137 | DIADEM: Thousands of Websites to a Single Database | 2014 | VLDB | 5.190481e-05 |
| 6,197 | WADaR: Joint Wrapper and Data Repair | 2015 | VLDB | 5.1570343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 853 | Integrating Conflicting Data: The Role of Source Dependence | 2009 | VLDB | 0.00015892569 |
| 3,679 | Automatic Wrappers for Large Scale Web Extraction | 2011 | VLDB | 6.8460927e-05 |
| 4,156 | Uncertainty Management in Rule-Based Information Extraction Systems | 2009 | SIGMOD | 6.3947765e-05 |
| 12,076 | ROSeAnn: Reconciling Opinions of Semantic Annotators | 2013 | VLDB | 4.1905499e-05 |
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