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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)

Paper ID
10687
Venue
VLDB
Year
2013
Pagerank
5.748807e-05
Overall Rank
5,032 | 65.00%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank Citing Paper Year Venue Pagerank
6,981 Dataset Relationship Management 2019 CIDR 4.8743957e-05
8,006 ALEX: Automatic Link Exploration in Linked Data 2015 SIGMOD 4.6080343e-05
8,696 Effective Entity Augmentation By Querying External Data Sources 2023 VLDB 4.4660032e-05
8,700 SeeSaw: Interactive Ad-hoc Search Over Image Databases 2023 SIGMOD 4.4656647e-05
9,278 Interactive and Deterministic Data Cleaning: A Tossed Stone Raises a Thousand Ripples 2016 SIGMOD 4.3639892e-05
9,696 The Data Interaction Game 2018 SIGMOD 4.3023337e-05
11,892 Looking at Everything in Context 2015 CIDR 4.1945683e-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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