Object Fusion in Geographic Information Systems

Summary: Introduces four location-only fusion algorithms to pairwise match objects across GIS databases despite imprecise locations and partial coverage. All four beat the one-sided nearest-neighbor join across varying density and overlap; one consistently best with modest extra run time. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h6fbdc51d6b09aeb6
Venue: VLDB
Year: 2004
Pagerank: 5.0979044e-05
Overall Rank: 10,011 | 32.70%
DOI: 10.1016/B978-012088469-8.50072-3

Incoming Non-self Citations Over Time

Authors

1. Catriel Beeri (Hebrew University)
2. Yaron Kanza (Hebrew University)
3. Eliyahu Safra (Hebrew University)
4. Yehoshua Sagiv (Hebrew University)

BibTeX Citation

@article{beeri_vldb04,
        title = {{Object Fusion in Geographic Information Systems}},
        author = {Beeri, Catriel and Kanza, Yaron and Safra, Eliyahu and Sagiv, Yehoshua},
        journal = {PVLDB},
        series = {{VLDB} '04},
        pages = {816--827},
        doi = {10.1016/B978-012088469-8.50072-3},
        url = {https://doi.org/10.1016/B978-012088469-8.50072-3},
        year = {2004}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
13,046	Database-Inspired Search	2005	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,190	Object Fusion in Mediator Systems	1996	VLDB	0.00011590876

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