Actively Soliciting Feedback for Query Answers in Keyword Search-Based Data Integration
Summary: Active learning for keyword-search-based data integration without a global schema, selecting top-k results for user feedback to learn correct integration. It predicts score uncertainty and informativeness of feedback to guide which results to label, validated on diverse real-domain data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhepeng Yan
- 2. Nan Zheng
- 3. Zachary G. Ives
- 4. Partha Pratim Talukdar
- 5. Cong Yu
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,980 | Dataset Relationship Management | 2019 | CIDR | 4.8696895e-05 |
| 8,010 | ALEX: Automatic Link Exploration in Linked Data | 2015 | SIGMOD | 4.6036121e-05 |
| 8,692 | Effective Entity Augmentation By Querying External Data Sources | 2023 | VLDB | 4.4617233e-05 |
| 8,694 | SeeSaw: Interactive Ad-hoc Search Over Image Databases | 2023 | SIGMOD | 4.4615833e-05 |
| 9,283 | Interactive and Deterministic Data Cleaning: A Tossed Stone Raises a Thousand Ripples | 2016 | SIGMOD | 4.3598353e-05 |
| 9,695 | The Data Interaction Game | 2018 | SIGMOD | 4.298211e-05 |
| 11,900 | Looking at Everything in Context | 2015 | CIDR | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 15 of 15 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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