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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)

Paper ID
9284
Venue
VLDB
Year
2004
Pagerank
5.2059956e-05
Overall Rank
9,859 | 32.36%
DOI
10.1016/B978-012088469-8.50136-4

Incoming Non-self Citations Over Time

Authors

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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