Information Discovery in Loosely Integrated Data
Summary: Models heterogeneous sources as a labeled data graph with typed nodes/edges. Introduces a relationship search operator (ObjectRank-based) that ranks objects related to a filter via link structure and builds summary graphs for results and reuse. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Heasoo Hwang (IBM; University of California San Diego)
- 2. Andrey Balmin (IBM)
- 3. Hamid Pirahesh (IBM)
- 4. Berthold Reinwald (IBM)
BibTeX Citation
@inproceedings{hwang_sigmod07,
title = {{Information Discovery in Loosely Integrated Data}},
author = {Hwang, Heasoo and Balmin, Andrey and Pirahesh, Hamid and Reinwald, Berthold},
series = {{SIGMOD} '07},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1247480.1247637},
url = {https://dl.acm.org/doi/10.1145/1247480.1247637},
year = {2007}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 285 | ObjectRank: Authority-Based Keyword Search in Databases | 2004 | VLDB | 0.00022365284 |
| 2,269 | GORDIAN: Efficient and Scalable Discovery of Composite Keys | 2006 | VLDB | 8.8328424e-05 |
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