Discovering and Ranking Semantic Associations over a Large RDF Metabase
Summary: Discovering and ranking Semantic Associations over a large RDF metabase. System discovers complex relationships among semantic metadata (RDF) and applies ranking to surface most meaningful associations. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chris Halaschek (University of Georgia)
- 2. Boanerges Aleman-Meza (University of Georgia)
- 3. I. Budak Arpinar (University of Georgia)
- 4. Amit P. Sheth (University of Georgia)
BibTeX Citation
@article{halaschek_vldb04,
title = {{Discovering and Ranking Semantic Associations over a Large RDF Metabase}},
author = {Halaschek, Chris and Aleman-Meza, Boanerges and Arpinar, I. Budak and Sheth, Amit P.},
journal = {PVLDB},
series = {{VLDB} '04},
volume = {30},
pages = {1317--1320},
doi = {10.1016/B978-012088469-8.50136-4},
url = {https://doi.org/10.1016/B978-012088469-8.50136-4},
year = {2004}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,052 | Top-k Relevant Semantic Place Retrieval on Spatial RDF Data | 2016 | SIGMOD | 5.1685424e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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|---|
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