Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration
Summary: Automatic appraisal and selection of valuable heterogeneous public data sources for integration under quality and cost constraints. Proposes a source-management system that computes rigorous quality metrics and enables automated/interactive discovery to shorten the discover–appraise–evaluate loop. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Theodoros Rekatsinas (University of Maryland)
- 2. Xin Luna Dong (Google)
- 3. Lise Getoor (University of California Santa Cruz)
- 4. Divesh Srivastava (AT&T)
BibTeX Citation
@inproceedings{rekatsinas_cidr15,
address = {Amsterdam, Netherlands},
series = {{CIDR} '15},
title = {{Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Rekatsinas, Theodoros and Dong, Xin Luna and Getoor, Lise and Srivastava, Divesh},
year = {2015}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,019 | SourceSight: Enabling Effective Source Selection | 2016 | SIGMOD | 5.3309706e-05 |
| 13,577 | StoryPivot: Comparing and Contrasting Story Evolution | 2015 | SIGMOD | - |
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Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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