Fusing Data with Correlations
Summary: Models correlations among sources beyond simple copying (positive/negative, cross-domain, extractor rules) to improve truth discovery in web-harvested data. Evaluated on three real/synthetic datasets, it outperforms state-of-the-art methods by robustly fusing noisy, conflicting web data. (summarized by gpt-5-nano on Feb 09 2026)
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,780 | Domain-Aware Multi-Truth Discovery from Conflicting Sources | 2018 | VLDB | 4.9277708e-05 |
| 11,770 | Staging User Feedback toward Rapid Conflict Resolution in Data Fusion | 2017 | SIGMOD | 4.1945683e-05 |
| 4,619 | Crowd-Based Deduplication: An Adaptive Approach | 2015 | SIGMOD | 6.0444854e-05 |
| 371 | A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration | 2012 | VLDB | 0.00025389696 |
| 2,617 | Extraction and Integration of Partially Overlapping Web Sources | 2013 | VLDB | 8.4462621e-05 |
| 3,824 | Correlation Sketches for Approximate Join-Correlation Queries | 2021 | SIGMOD | 6.7260705e-05 |
| 2,686 | Online Data Fusion | 2011 | VLDB | 8.3053595e-05 |
| 5,094 | Global Detection of Complex Copying Relationships Between Sources | 2010 | VLDB | 5.7023083e-05 |
| 2,420 | From Data Fusion to Knowledge Fusion | 2014 | VLDB | 8.8530994e-05 |
| 855 | Integrating Conflicting Data: The Role of Source Dependence | 2009 | VLDB | 0.00015906735 |